Datasets:

G-reen
/

cc-re-2021-stat-val

original stringlengths 242 39.4k	prompt dict	response_0 stringlengths 9 39.2k	response_1 stringlengths 0 21.9k	generator_model stringclasses 1 value	generation_params stringclasses 1 value	final_response stringlengths 51 24.3k	jaccard_1 float64 0 0.99	jaccard_2 float64 0 1	levenshtein float64 1 37.8k	softngram float64 0 1	cosdist float64 -0.01 1.02	bertscore_precision float64 0 0.38	bertscore_recall float64 0 0.43	bertscore float64 0 0.36	moverscore float64 0.08 0.94	reranker float64 -10.44 17.1	original_perplexity_llama_instruct float64 2.13 101	original_entropy_llama_instruct float64 0.71 4.71	original_topp_outlier_llama_instruct float64 0.01 0.15	original_topk_outlier_llama_instruct float64 0 0.31	original_fastdetectgpt_llama_instruct float64 -11.5 6.38	original_perplexity_llama_base float64 1.03 76.3	original_entropy_llama_base float64 0.06 4.16	original_topp_outlier_llama_base float64 0 0.11	original_topk_outlier_llama_base float64 0 0.31	original_fastdetectgpt_llama_base float64 -4.17 4.22	final_response_perplexity_llama_instruct float64 2.02 677	final_response_entropy_llama_instruct float64 0.52 5.32	final_response_topp_outlier_llama_instruct float64 0 0.28	final_response_topk_outlier_llama_instruct float64 0 0.55	final_response_fastdetectgpt_llama_instruct float64 -8.6 4.88	final_response_perplexity_llama_base float64 1.65 432	final_response_entropy_llama_base float64 0.48 4.89	final_response_topp_outlier_llama_base float64 0 0.2	final_response_topk_outlier_llama_base float64 0 0.55	final_response_fastdetectgpt_llama_base float64 -11.25 4.24	original_binoculars float64 0.01 1.11	final_response_binoculars float64 0.17 1.32	original_editlens_bucket_roberta_large int64 0 3	original_editlens_score_roberta_large float64 0.01 0.98	final_response_editlens_bucket_roberta_large int64 0 3	final_response_editlens_score_roberta_large float64 0.01 1
Professional appraisers offer services to residential real estate clients as well as commercial clients. An appraiser can help answer all the questions you have about pricing your property. You need to understand that pricing a home can be tricky without the help of an appraiser. If you want to sell a home or get invol...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nEdit this text by replacing five to ten percent of words in it, without changing anything else.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming what yo...	Expert evaluators provide assistance to residential and commercial real estate customers. Engaging the services of an assessor can help you address all inquiries related to pricing your property. It's essential to recognize that determining a home's price can be challenging without the guidance of an evaluator. If you...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Expert evaluators provide assistance to residential and commercial real estate customers. Engaging the services of an assessor can help you address all inquiries related to pricing your property. It's essential to recognize that determining a home's price can be challenging without the guidance of an evaluator. If you ...	0.70411	0.883784	1,517	0.75168	0.146171	0.145844	0.11868	0.132475	0.553007	-5.3125	8.19709	2.027131	0.046512	0.041528	-1.011381	7.159292	2.038516	0.038206	0.033223	0.91035	11.31123	2.286379	0.048986	0.069257	-1.71889	9.952746	2.232721	0.040541	0.057432	-0.840104	0.898847	0.926964	0	0.137056	1	0.32604
whilst you’re, y’know, plotting your metabolism and immune system, and feature spectacular curative results on high, using very fresh, biological flavor of home made broth, the How To Make Bone Broth In The Slow Cooker? If using beef bones, then strain stock and discard them 1opyright 2014 The Real Food Guide I went to...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nClarify this text by defining any terms that might be unclear to the reader.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming what you have written." ...	While making bone broth in a slow cooker can have impressive benefits for your metabolism and immune system, there are a few things to consider when following the guide for "How To Make Bone Broth In The Slow Cooker." The guide suggests that if using beef bones, you should strain the stock and discard them after cooki...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	While making bone broth in a slow cooker can have impressive benefits for your metabolism and immune system, there are a few things to consider when following the guide for "How To Make Bone Broth In The Slow Cooker." The guide suggests that if using beef bones, you should strain the stock and discard them after cookin...	0.835539	0.958643	3,700	0.667033	0.455473	0.214243	0.280495	0.248827	0.812741	6.3125	54.841072	4.353342	0.042593	0.25463	4.269051	42.21776	3.675229	0.049074	0.222222	-0.884397	7.830434	2.047077	0.050314	0.056604	-0.101632	7.042774	2.065801	0.040881	0.056604	1.088919	0.799691	0.839506	0	0.007969	1	0.421351
If there’s something strange in your neighbourhood, who you gonna call? Well until now it was Bill Murray, Dan Aykroyd and Harold Ramis, not now, as we have the reboot of the 1984 classic with 4 woman in the leading roles. Despite the foreboding, this is a thoroughly enjoyable popcorn movie directed by Paul Feig whose ...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nEdit this text by inserting twenty to thirty words (in appropriate locations), without changing anything else.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label...	If there’s something strange in your neighborhood, you might consider calling the new Ghostbusters team, led by four women who take on the task of capturing ghosts in this updated reboot of the 1984 classic. Directed by Paul Feig, known for his work on Bridesmaids, the film boasts sharp dialogue, snappy one-liners, an...	Undoubtedly, if you detect something peculiar in your vicinity, you may think about contacting the latest Ghostbusters squad, spearheaded by a female quartet who tackle the job of apprehending ghosts in this modernized adaptation of the 1984 classic. Supervised by Paul Feig, recognized for his endeavors on Bridesmaids...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Undoubtedly, if you detect something peculiar in your vicinity, you may think about contacting the latest Ghostbusters squad, spearheaded by a female quartet who tackle the job of apprehending ghosts in this modernized adaptation of the 1984 classic. Supervised by Paul Feig, recognized for his endeavors on Bridesmaids,...	0.839535	0.946746	2,200	0.76977	0.145174	0.152886	0.176804	0.165016	0.614426	-7.5625	18.101822	2.965338	0.054012	0.126543	0.747955	13.268478	2.581988	0.050926	0.103395	-0.039123	17.859226	2.979704	0.040752	0.15674	0.747914	14.088074	2.663391	0.040752	0.137931	0.14259	0.765861	0.786126	0	0.011723	3	0.716795
The Studio Assistant: Louise Nevelson & Teddy Haseltine Our June 25 sale of Contemporary Art features a run of prints by Louise Nevelson. Behind great artists are studio assistants equally devoted to their craft. For Nevelson one of those assistants was Teddy Haseltine. Meagan Gandolfo, one of our cataloguers for the p...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nClarify this text by improving the phrasing while preserving its original intent.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming what you have written...	The Contemporary Art sale on June 25 includes a series of prints by Louise Nevelson, whose studio assistant was Teddy Haseltine. Meagan Gandolfo, a cataloguer in Swann Galleries' prints and drawings department, explores the collaborative relationship between Nevelson and Haseltine throughout Nevelson's career. Teddy ...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	The Contemporary Art sale on June 25 includes a series of prints by Louise Nevelson, whose studio assistant was Teddy Haseltine. Meagan Gandolfo, a cataloguer in Swann Galleries' prints and drawings department, explores the collaborative relationship between Nevelson and Haseltine throughout Nevelson's career. Teddy Ha...	0.614532	0.797954	3,320	0.276723	0.025282	0.069908	0.080672	0.075321	0.4047	-7.1875	12.846158	2.651318	0.039663	0.108774	1.889955	10.532413	2.300439	0.042668	0.091346	-1.108431	11.705226	2.513918	0.044309	0.119175	0.945197	10.269466	2.218527	0.047364	0.101604	-2.090878	0.803334	0.843439	0	0.06601	1	0.380199
Our research library is home to a large inventory of historical and genealogical books and publications. It contains books and publications from most if not all of the fifty states. We have many surname books, family history compilations, family folders, historical newspapers, military books and index publications, and...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nWrite a different piece of text on the same topic.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming what you have written." ], "use_multiturn": fals...	Welcome to our research library, which houses an extensive collection of historical and genealogical materials from various regions across the United States. Our holdings include numerous surname books, family history compilations, genealogical folders, historical newspapers, military records, and a wide variety of ot...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Welcome to our research library, which houses an extensive collection of historical and genealogical materials from various regions across the United States. Our holdings include numerous surname books, family history compilations, genealogical folders, historical newspapers, military records, and a wide variety of oth...	0.714286	0.916667	475	0.447044	0.357781	0.134553	0.109509	0.12221	0.546327	-4.6875	20.127203	2.570373	0.048387	0.112903	-2.277542	14.813693	2.732821	0.032258	0.064516	0.195822	11.040225	2.072136	0.080537	0.060403	-2.155281	10.39227	2.257442	0.04698	0.053691	-0.526102	0.933533	0.943007	0	0.015447	1	0.312632
The character in a first- or third-person game will often need some collision-based physics so that it doesn’t fall through the floor or walk through walls. Usually, though, the character’s acceleration and movement will not be physically realistic, so it may be able to accelerate, brake and change direction almost ins...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nCreate a prompt that would allow an LLM to generate this text as accurately/verbatim as possible, without the prompt containing any of the actual text. That is, you must use descriptors to accurately describe the text to generate.\nDo not output anything besi...	Generate a description of a system used in video games for controlling character movement within a 3D environment, highlighting how it differs from traditional physics systems. Describe the use of a "Character Controller" component that provides a simplified, upright collider and specialized functions for setting spee...	In video games, controlling character movement within a 3D environment often involves a unique system that differs from traditional physics systems. This specialized approach is designed to provide an intuitive and enjoyable experience for players, while still maintaining a sense of realism. A key component of this sy...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	In video games, controlling character movement within a 3D environment often involves a unique system that differs from traditional physics systems. This specialized approach is designed to provide an intuitive and enjoyable experience for players, while still maintaining a sense of realism. A key component of this sys...	0.85034	0.978632	1,546	0.93747	0.270003	0.208011	0.161579	0.185456	0.66652	4.25	21.233168	2.688019	0.064815	0.092593	-2.440587	16.115049	2.702446	0.055556	0.074074	-0.523304	7.645469	1.819729	0.046961	0.033149	-2.22693	7.749456	1.869227	0.038674	0.033149	-1.877866	0.945094	0.942204	0	0.028637	3	0.999532
Rooted inPennsylvania's rural beginnings, this trail leads to pastoral landscapes from Colonial to recent history. Escaping into the sylvan settings is as simple as joining a tour. To truly live the history, you'll want to take part in special events throughout the year that recall the craft and culinary heritage of ce...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nEdit this text by inserting twenty to thirty words (in appropriate locations), without changing anything else.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label...	Rooted in Pennsylvania's rich rural beginnings, the trail offers an escape into serene sylvan settings that span from Colonial to recent history. Joining a tour provides easy access to these pastoral landscapes, but to truly experience the region's historical charm, consider participating in special events held throug...	Steeped in Pennsylvania's verdant rural origins, the trail beckons visitors to plunge into tranquil woodland vistas that stretch from Colonial times to recent history. Embarking on a specialized tour grants effortless access to these idyllic landscapes; however, to fully savor the region's historical allure, partaking...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Steeped in Pennsylvania's verdant rural origins, the trail beckons visitors to plunge into tranquil woodland vistas that stretch from Colonial times to recent history. Embarking on a specialized tour grants effortless access to these idyllic landscapes; however, to fully savor the region's historical allure, partaking ...	0.851429	0.962185	874	0.911392	0.160516	0.244689	0.185877	0.216385	0.713189	-1.625	34.812546	3.406815	0.029412	0.196078	-0.553161	26.011586	3.302874	0.009804	0.156863	0.179269	24.45572	3.139457	0.044643	0.1875	-0.380544	19.228806	2.89684	0.03125	0.183036	-0.399852	0.871024	0.858538	0	0.092496	3	0.919236
Casino payouts or perhaps one of the most complicated things to factor in when playing competitive online casino games like poker, slot machines, and blackjack. All of these games operating different manners and have different payouts requirements for each of the type of games that are factored in. For example, a stand...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nWrite a prequel to this text, describing the events, thoughts, or historical context that immediately led up to this piece being written, making sure to use similar language and wording as the author, as if it was written by the author.\nOutput the full new t...	Deciding to try your luck at online casinos can be both exciting and daunting. With so many games to choose from, each with its own set of rules and payout structures, it's easy to feel overwhelmed. One crucial aspect to consider before diving in is understanding the payout rates of the games you're interested in. Be...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Deciding to try your luck at online casinos can be both exciting and daunting. With so many games to choose from, each with its own set of rules and payout structures, it's easy to feel overwhelmed. One crucial aspect to consider before diving in is understanding the payout rates of the games you're interested in. Befo...	0.763889	0.940397	2,977	0.619869	0.212818	0.164735	0.187048	0.176042	0.646051	-0	11.203721	2.345976	0.058691	0.057562	-0.987366	9.552022	2.22404	0.053047	0.054176	-0.485788	5.272073	1.535464	0.052133	0.040284	-1.59599	5.041041	1.469054	0.045024	0.033175	-1.948422	0.881367	0.871435	0	0.010561	3	0.998925
Google Assistant can do a lot of awesome things, but that list would be much shorter without developer support. That's what Actions on Google is all about—it helps developers integrate apps and services with Assistant. Thus, you can shout at your phone and smart speakers more often. Now, developers can start supporting...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nCreate a prompt that might cause an LLM to generate an output resembling this text.\nDo not output anything besides what you were requested to write, and do not output any extra commentary.", "{{RESP_0}}\nOutput only the generated text with no extra comme...	"How does Actions on Google enable developer support for Google Assistant, and what are the current capabilities for the Chinese (traditional) language?"	Actions on Google is a platform that enables developers to build conversational experiences for Google Assistant. It provides tools, documentation, and APIs for developers to create Actions, which are responses or functionalities that the Google Assistant can perform based on user requests. These Actions can include c...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Actions on Google is a platform that enables developers to build conversational experiences for Google Assistant. It provides tools, documentation, and APIs for developers to create Actions, which are responses or functionalities that the Google Assistant can perform based on user requests. These Actions can include cu...	0.873737	0.972125	819	0.907712	0.250506	0.202127	0.206327	0.204232	0.697583	5.375	27.22929	2.697706	0.114155	0.123288	-4.042721	18.603352	2.654854	0.054795	0.100457	-1.872209	7.139687	1.669261	0.047945	0.027397	-2.12012	7.436019	1.848483	0.068493	0.027397	-1.076853	0.963748	0.956013	1	0.29939	0	0.430314
Our cookies ensure you get the best experience on our website. Please make your choice! Some cookies are necessary in order to make this website function correctly. These are set by default and whilst you can block or delete them by changing your browser settings, some functionality such as being able to log in to the ...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nRewrite only the opening hook and the final concluding sentence of this text, leaving the entire middle portion exactly as it was originally written.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do...	Experience our website to its fullest potential with the necessary cookies. While these cannot be blocked or deleted without affecting functionality like login, optional cookies that enhance features can be enabled at your discretion. These additional cookies are disabled by default and primarily serve to differentiat...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Experience our website to its fullest potential with the necessary cookies. While these cannot be blocked or deleted without affecting functionality like login, optional cookies that enhance features can be enabled at your discretion. These additional cookies are disabled by default and primarily serve to differentiate...	0.795918	0.951613	870	0.734827	0.252918	0.175418	0.204884	0.190419	0.668764	-0.625	7.632482	1.851526	0.063291	0.029536	-1.439105	4.070363	1.546901	0.025316	0.016878	1.279246	17.429143	2.669614	0.050279	0.083799	-1.182286	17.206231	2.577416	0.061453	0.089385	-1.746885	0.510298	0.942881	0	0.020177	3	0.938332
Nearly half of all children in the United States will be the subject of custody proceedings. When Mississippi parents separate or divorce, the hardest part of the process is determining the best custody arrangement for their minor children. In some instances, a child's preference can change the outcome of a custody cas...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nClarify this text by making the cause-and-effect relationships more obvious.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming what you have written." ...	When Mississippi parents separate or divorce, determining the best custody arrangement for their minor children can be challenging. If parents can reach their own custody agreements, they can avoid the hassle and expense of attending trial. In cases where parents don't agree, a judge will decide both physical and lega...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	When Mississippi parents separate or divorce, determining the best custody arrangement for their minor children can be challenging. If parents can reach their own custody agreements, they can avoid the hassle and expense of attending trial. In cases where parents don't agree, a judge will decide both physical and legal...	0.721739	0.856287	4,727	0.152346	0.144382	0.080969	0.161125	0.122874	0.574266	-3.8125	6.85955	1.772275	0.053815	0.035341	-2.954412	5.796338	1.696773	0.046586	0.027309	-1.249456	7.281581	1.619947	0.067278	0.024465	-4.006527	5.896883	1.851097	0.030581	0.018349	0.819829	0.883916	0.931169	0	0.055065	3	0.818241
After a year of seasonal influences, with extreme differences in temperature, combined with a long period of drought, the green wall at the testing site appeared to be withered. In September the plants were replaced and the new green wall is a feast for the eye. At the same time the modest sedum plants on the roof are ...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nWrite an alternate version of this text, it should follow the style and format of the original text.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming wh...	Following a year of significant temperature fluctuations and a protracted dry spell, the green wall at the test location showed signs of deterioration. In September, new plants were introduced, and the revitalized green wall now serves as a delightful visual treat. Similarly, the sturdy sedum plants on the rooftop hav...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Following a year of significant temperature fluctuations and a protracted dry spell, the green wall at the test location showed signs of deterioration. In September, new plants were introduced, and the revitalized green wall now serves as a delightful visual treat. Similarly, the sturdy sedum plants on the rooftop have...	0.835938	0.911602	409	0.685714	0.45167	0.173116	0.154187	0.163758	0.5894	-2.3125	32.109957	3.353733	0.042735	0.188034	-0.501958	23.557363	3.421764	0.034188	0.162393	1.16208	22.765293	3.140653	0.032787	0.172131	0.070875	20.727791	3.203673	0.032787	0.163934	0.818541	0.867905	0.872119	0	0.022604	3	0.999547
Jimmy Armfield is widely regarded as the first overlapping full-back. The pioneering right-back used to get forward at every opportunity in an era where players in his position rarely ventured beyond the half-way line. Armfield joined his local side Blackpool as a teenager in 1954, where he played behind the great Stan...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nEnvision the scenario in which the author wrote this text. Describe that scenario in exhaustive detail.\nDo not output anything besides what you were requested to write, and do not output any extra commentary.", "{{RESP_0}}\nAbove is an AI generated descr...	The author of the text, presumably a football (soccer) enthusiast or a journalist, is recounting the life and career of Jimmy Armfield, a renowned English full-back who played for Blackpool and England. The author has likely conducted research on Armfield's life, including interviews with the player himself, teammates...	Jimmy Armfield, a name synonymous with dedication, skill, and sportsmanship in the world of English football, was born in the coastal town of Denton, Lancashire, in 1935. His professional footballing journey began at the age of 17 when he signed with Blackpool Football Club, starting as an amateur in 1950 before turni...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Jimmy Armfield, a name synonymous with dedication, skill, and sportsmanship in the world of English football, was born in the coastal town of Denton, Lancashire, in 1935. His professional footballing journey began at the age of 17 when he signed with Blackpool Football Club, starting as an amateur in 1950 before turnin...	0.880903	0.983073	2,150	0.980169	0.19284	0.244901	0.181664	0.214553	0.728066	-0.625	11.771095	2.409476	0.044118	0.069853	-0.619091	9.296018	2.30307	0.023897	0.058824	0.875215	3.240409	1.136562	0.02568	0.021148	-0.694316	3.111377	1.226005	0.015106	0.016616	1.59751	0.813142	0.784181	0	0.061037	1	0.399851
The Korean manufacturer Samsung offers a whole range of smart TVs and Tizen has been used as the operating system for a while. This not only has friends but if you have no problem with it, the new smart monitors may be of interest. A computer screen is usually one thing: a screen. The reason for this can already be fou...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nWrite a 'few-shot' prompt using minimal, fragmented excerpts from this text as examples. The prompt should be designed to teach an LLM the pattern needed to generate the rest of the text from scratch.\nDo not output anything besides what you were requested to...	Prompt: Title: Samsung's New Smart Monitors Excerpt 1: "The Korean manufacturer Samsung offers a whole range of smart TVs and Tizen has been used as the operating system for a while..." Excerpt 2: "[...] the new smart monitors may be of interest. A computer screen is usually one thing: a screen... Nevertheless, Sam...	The new Samsung smart monitors aim to cater to a wide range of users, including professionals working from home, casual gamers, and those seeking an all-in-one solution for both work and entertainment. These smart monitors combine the functionalities of traditional computer monitors and smart TVs, offering users a sea...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	The new Samsung smart monitors aim to cater to a wide range of users, including professionals working from home, casual gamers, and those seeking an all-in-one solution for both work and entertainment. These smart monitors combine the functionalities of traditional computer monitors and smart TVs, offering users a seam...	0.865014	0.960199	1,813	0.91848	0.362702	0.227457	0.198472	0.213231	0.707398	6.625	14.931647	2.627546	0.036554	0.099217	-0.657026	11.600737	2.580536	0.018277	0.060052	1.17323	4.533273	1.267103	0.053452	0.011136	-3.522037	4.370529	1.478796	0.028953	0.020045	0.052647	0.841808	0.946168	0	0.019654	3	0.999389
So, surrender to sleep at last. What a misery keeping watch through the night, wide awake - you'll soon come up from under all your troubles. Artemis - goddess, noble daughter of Zeus, if only you's whip an arrow through my breast and tear my life out, now, at once! I still dream of my old master, unlucky man - if only...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nChange the tone of this text to be more inspiring and motivational.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming what you have written.", "{{RES...	Embrace the rest that sleep brings, leaving behind the weariness of watching through the night. Artemis, noble daughter of Zeus, may your guiding light illuminate our path, providing strength and courage when we need it most. May we always remember the lessons taught by those who came before us, like the unforgettable...	Embrace the rest that sleep brings, allowing your mind and body to rejuvenate after a long day. Just as the moon passes through phases, so too does our energy wax and wane; recognize the importance of recognizing one's limits and giving oneself permission to rest (National Sleep Foundation, 2021). By doing so, you wil...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Embrace the rest that sleep brings, allowing your mind and body to rejuvenate after a long day. Just as the moon passes through phases, so too does our energy wax and wane; recognize the importance of recognizing one's limits and giving oneself permission to rest (National Sleep Foundation, 2021). By doing so, you will...	0.944798	0.99705	2,558	0.998207	0.48578	0.264119	0.222076	0.243681	0.74848	5.6875	43.106283	3.402209	0.081481	0.185185	-2.534096	34.140908	3.347624	0.051852	0.17037	-1.296892	6.864111	1.729068	0.062903	0.053226	-2.834949	6.711719	1.953382	0.027419	0.048387	0.687869	0.940695	0.916126	0	0.154366	3	0.660436
We're people. People have feelings. Feelings make you do things. Things that are not always the best things. The comment section. It's where angry people go to express how angry they are at whatever they're commenting on. Unfortunately, one of the side effects of anger is that it makes you dumb. No really, it does. Ang...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nWrite a different piece of text on the same topic.\nOutput the full new text with no extra statements or commentations.\nBegin directly with the text itself. Do not add a title, a heading, or a label naming what you have written." ], "use_multiturn": fals...	Anger and other strong emotions can greatly impact our behavior, especially in online environments. When people are angry, they often use simplified thinking patterns instead of engaging in more thorough reasoning. They are also more likely to blame individuals for problems, rather than considering situational factors...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	Anger and other strong emotions can greatly impact our behavior, especially in online environments. When people are angry, they often use simplified thinking patterns instead of engaging in more thorough reasoning. They are also more likely to blame individuals for problems, rather than considering situational factors....	0.854922	0.969136	1,947	0.852121	0.460084	0.217779	0.24599	0.232143	0.738887	2.6875	14.376932	2.466632	0.044643	0.089286	-2.170179	11.045027	2.46433	0.039286	0.069643	0.705046	5.303003	1.640769	0.029032	0.03871	-0.276891	5.226246	1.906048	0.009677	0.041935	2.519203	0.858847	0.841513	0	0.165167	3	0.908411
PRODUCER FEATURE – GRUYERE ALPAGE FROM RIGGISALP DAIRY Production of Gruyere dates back to at least 1115, making it one of the world’s oldest cheeses. If we were to take a time machine back to a time before electricity and modern machinery, we would find Swiss farmers making cheese in almost the exact same manner Gruye...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nEdit this text by inserting exactly one to three sentences (in appropriate locations), you may only make minimal modifications to transitions in adjacent sentences for better flow.\nOutput the full new text with no extra statements or commentations.\nBegin di...	PRODUCER FEATURE – GRUYERE ALPAGE FROM RIGGISALP DAIRY Production of Gruyere dates back to at least 1115, making it one of the world’s oldest cheeses. If we were to take a time machine back to a time before electricity and modern machinery, we would find Swiss farmers making cheese in almost the exact same manner Gru...	What makes Gruyere Alpage so unique? Numerous factors contribute to its distinctiveness. The cows that provide the milk for Alpage cheeses spend their summers in Alpine meadows, feeding on a diverse diet of fresh and moist mountain grasses, herbs, and wildflowers. This results in milk with a particular terroir that sh...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	What makes Gruyere Alpage so unique? Numerous factors contribute to its distinctiveness. The cows that provide the milk for Alpage cheeses spend their summers in Alpine meadows, feeding on a diverse diet of fresh and moist mountain grasses, herbs, and wildflowers. This results in milk with a particular terroir that sha...	0.611015	0.750467	1,839	0.300998	0.059617	0.078762	0.087356	0.083079	0.419331	-5.5625	15.356617	2.554615	0.059921	0.096267	-2.59807	11.890536	2.401524	0.052063	0.08055	-1.156044	13.945448	2.523323	0.054526	0.094875	-1.573614	11.064921	2.345474	0.047983	0.081788	-0.878693	0.876997	0.859604	0	0.022651	1	0.277267
This was built in to address some of the issues found with the Mark 1 version. The main differences are: The main axle of 10mm stud is replaced with length of 10mm steel rod, threaded at both ends. The components (hub bearings, alternator, body, etc) are clamped along the length of the axle spaced with sections of 12mm...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nCreate a prompt that would allow an LLM to generate this text as accurately/verbatim as possible, without the prompt containing any of the actual text. That is, you must use descriptors to accurately describe the text to generate.\nDo not output anything besi...	Generate a description of the improvements made in a newer version of a small turbine, as compared to its previous version. Begin by describing how the main axle has been upgraded from a 10mm stud to a 10mm steel rod, threaded at both ends, with components such as hub bearings, alternator, and body clamped along its l...	The main axle in the newer version of the small turbine has undergone significant upgrades, replacing the 10mm stud with a 10mm steel rod, now threaded at both ends. This change ensures a more secure and precise fitting for the hub bearings, alternator, and body, which are held in place along the length of the steel r...	mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	The main axle in the newer version of the small turbine has undergone significant upgrades, replacing the 10mm stud with a 10mm steel rod, now threaded at both ends. This change ensures a more secure and precise fitting for the hub bearings, alternator, and body, which are held in place along the length of the steel ro...	0.77907	0.922794	717	0.764014	0.252132	0.194714	0.156941	0.17626	0.630964	-3.4375	21.794905	3.093188	0.050847	0.141243	0.061909	16.464597	3.105669	0.045198	0.107345	1.70961	18.305958	2.796539	0.064677	0.104478	-0.70693	16.561221	2.778405	0.044776	0.084577	-0.190284	0.823726	0.916296	0	0.011732	3	0.997202
We've thoroughly reviewed DuckDice Casino and gave it a very good reputation rating, which means it's a great casino to play at. In our review, we've considered the casino's player complaints, estimated revenues, license, games genuineness, customer support quality, fairness of terms and conditions, withdrawal and win ...	{ "chat_turns": [ "<document>\n{{DOC}}\n</document>\n\nEdit this text by inserting exactly one to three sentences (in appropriate locations), you may only make minimal modifications to transitions in adjacent sentences for better flow.\nOutput the full new text with no extra statements or commentations.\nBegin di...	DuckDice Casino is a platform that focuses on dice games, offering a unique and engaging gaming experience. Despite its smaller size, the casino has no relevant complaint records, indicating a commitment to player satisfaction. With positive reviews and estimations, DuckDice Casino proves to be a reliable choice for p...		mistralai/Mixtral-8x7B-Instruct-v0.1	{"temperature": 0.7, "top_p": 0.95, "extra_body": {"top_k": 40, "repetition_penalty": 1.1, "chat_template_kwargs": {"enable_thinking": false}}}	DuckDice Casino is a platform that focuses on dice games, offering a unique and engaging gaming experience. Despite its smaller size, the casino has no relevant complaint records, indicating a commitment to player satisfaction. With positive reviews and estimations, DuckDice Casino proves to be a reliable choice for pl...	0.303448	0.365	487	0.26738	0.142901	0.066846	0.04864	0.057831	0.364254	-2.4375	9.218264	1.810462	0.067358	0.056995	-2.989192	1.555799	0.465965	0.010363	0.015544	0.310091	8.145876	1.731812	0.080169	0.067511	-3.031014	2.738458	0.946675	0.033755	0.033755	-0.684157	0.071303	0.225722	0	0.012069	1	0.335516

End of preview. Expand in Data Studio

Auto-Generated FastDetector Dataset

Dataset: G-reen/cc-re-2021-stat-val
Globals Config: config/globals_re2021.toml
Analysis Config: config/analysis_nofilter.toml
Rows: 9,822

Evaluation Results

Prompt Subsets: 4 (direct_reference, indirect_reference, revise, rewrite)
Generator Configs: 5 (Hy3-NVFP4-FP8 (Temp: 0.9), Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6), Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7), claude-sonnet-5 (Temp: Unknown), gpt-5.6-luna (Temp: Unknown))
Classifiers: 13 (EditLens Roberta-Large Score, EditLens Roberta-Large Bucket, Perplexity (Llama-3.2-3B-Instruct), Perplexity (Llama-3.2-3B), Entropy (Llama-3.2-3B-Instruct), Entropy (Llama-3.2-3B), Top-p Outliers (Llama-3.2-3B-Instruct), Top-p Outliers (Llama-3.2-3B), Top-k Outliers (Llama-3.2-3B-Instruct), Top-k Outliers (Llama-3.2-3B), FastDetectGPT (Llama-3.2-3B-Instruct), FastDetectGPT (Llama-3.2-3B), Binoculars)
Filter Conditions: None
Evaluation / Validation Rows: 8,839 / 983 (validation_size = 0.1)
Base Columns: original (Human), final_response (AI)

The best classifier was EditLens Roberta-Large Score with an AUROC of 0.8623. The hardest prompt subset was rewrite with a TPR of 0.0384, and the hardest generator config was Hy3-NVFP4-FP8 (Temp: 0.9) with a TPR of 0.0542.

Classifier	Threshold	AUROC	TPR	FPR	Accuracy	F1
✔️ EditLens Roberta-Large Score	0.8261	0.8623	0.2073	0.0023	0.6025	0.3427
EditLens Roberta-Large Bucket	0.0000	0.7646	0.5737	0.0579	0.7579	0.7032
Entropy (Llama-3.2-3B-Instruct)	1.4754	0.6384	0.0815	0.0063	0.5376	0.1498
Perplexity (Llama-3.2-3B-Instruct)	4.8037	0.6340	0.0753	0.0038	0.5358	0.1396
Top-k Outliers (Llama-3.2-3B-Instruct)	0.0172	0.6128	0.0428	0.0025	0.5201	0.0818
Top-p Outliers (Llama-3.2-3B)	0.0034	0.6123	0.0050	0.0041	0.5005	0.0099
Binoculars	1.0087	0.6085	0.0303	0.0091	0.5106	0.0583
Perplexity (Llama-3.2-3B)	1.2354	0.5923	0.0001	0.0019	0.4991	0.0002
Top-k Outliers (Llama-3.2-3B)	0.0012	0.5792	0.0009	0.0007	0.5001	0.0018
Entropy (Llama-3.2-3B)	0.2195	0.5758	0.0002	0.0020	0.4991	0.0005
Top-p Outliers (Llama-3.2-3B-Instruct)	0.0275	0.5277	0.0354	0.0081	0.5136	0.0679
FastDetectGPT (Llama-3.2-3B-Instruct)	3.3428	0.4990	0.0038	0.0069	0.4985	0.0076
❗ FastDetectGPT (Llama-3.2-3B)	-3.1816	0.3950	0.0089	0.0037	0.5026	0.0177

Classifier metrics averaged within each prompt and generator subset:

Subset	Average AUROC	Average TPR	Average FPR	Average Accuracy	Average F1
✔️ Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	0.6706	0.1336	0.0094	0.5621	0.1817
Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	0.6606	0.1047	0.0078	0.5484	0.1625
Prompt: indirect_reference	0.6370	0.0916	0.0085	0.5416	0.1402
Prompt: direct_reference	0.6335	0.1105	0.0078	0.5513	0.1595
Prompt: revise	0.6257	0.0822	0.0087	0.5367	0.1066
Model: gpt-5.6-luna (Temp: Unknown)	0.6123	0.0578	0.0091	0.5244	0.0815
Model: claude-sonnet-5 (Temp: Unknown)	0.5951	0.0598	0.0075	0.5261	0.0848
Prompt: rewrite	0.5283	0.0384	0.0087	0.5148	0.0621
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	0.5027	0.0542	0.0084	0.5229	0.0800

✔️ marks the best AUROC, ❗ the worst.

Statistics of Interest

Appendix

Table of contents

Univariate Analysis

Correlation Heatmap

Distance Histograms

Distance Histograms per Prompt Subset

Distance Histograms per Generator Config Subset

Classifier: EditLens Roberta-Large Score

Performance:

Thresholding:

Classification Histograms:

Classifier: EditLens Roberta-Large Bucket

Performance:

Thresholding:

Classification Histograms:

Classifier: Perplexity (Llama-3.2-3B-Instruct)

Performance:

Thresholding:

Classification Histograms:

Classifier: Perplexity (Llama-3.2-3B)

Performance:

Thresholding:

Classification Histograms:

Classifier: Entropy (Llama-3.2-3B-Instruct)

Performance:

Thresholding:

Classification Histograms:

Classifier: Entropy (Llama-3.2-3B)

Performance:

Thresholding:

Classification Histograms:

Classifier: Top-p Outliers (Llama-3.2-3B-Instruct)

Performance:

Thresholding:

Classification Histograms:

Classifier: Top-p Outliers (Llama-3.2-3B)

Performance:

Thresholding:

Classification Histograms:

Classifier: Top-k Outliers (Llama-3.2-3B-Instruct)

Performance:

Thresholding:

Classification Histograms:

Classifier: Top-k Outliers (Llama-3.2-3B)

Performance:

Thresholding:

Classification Histograms:

Classifier: FastDetectGPT (Llama-3.2-3B-Instruct)

Performance:

Thresholding:

Classification Histograms:

Classifier: FastDetectGPT (Llama-3.2-3B)

Performance:

Thresholding:

Classification Histograms:

Classifier: Binoculars

Performance:

Thresholding:

Classification Histograms:

Univariate Analysis

Every statistic the report does arithmetic on, over the 8,839-row evaluation split. Invalid counts rows whose value is missing or non-finite; those rows are excluded from the other columns.

Statistic	N	Mean	Median	Std	Min	Max
jaccard_1	8,839	0.6076	0.7128	0.2768	0.0000	1.0000
jaccard_2	8,839	0.7274	0.8750	0.2992	0.0000	1.0000
levenshtein	8,839	2109.1352	1222.0000	3177.3081	1.0000	63409.0000
softngram	8,839	0.5287	0.5714	0.3462	0.0000	1.0000
cosdist	8,839	0.1692	0.0990	0.1874	-0.0073	1.0241
bertscore	8,839	0.1265	0.1351	0.0748	0.0001	0.6915
bertscore_precision	8,839	0.1225	0.1282	0.0731	0.0001	0.6779
bertscore_recall	8,839	0.1294	0.1353	0.0813	0.0000	0.7040
moverscore	8,839	0.5068	0.5647	0.1998	0.0397	1.2479
reranker	8,839	-4.4972	-6.6875	5.3779	-11.3125	17.1250
EditLens Roberta-Large Score (Human)	8,839	0.0581	0.0203	0.0965	0.0063	0.9996
EditLens Roberta-Large Score (AI)	8,839	0.4077	0.3069	0.3496	0.0064	0.9996
EditLens Roberta-Large Bucket (Human)	8,839	0.0677	0.0000	0.3038	0.0000	3.0000
EditLens Roberta-Large Bucket (AI)	8,839	1.1323	1.0000	1.2337	0.0000	3.0000
Perplexity (Llama-3.2-3B-Instruct) (Human)	8,839	18.5745	15.7332	12.8903	1.7117	630.4184
Perplexity (Llama-3.2-3B-Instruct) (AI)	8,839	15.6951	12.5905	19.4628	1.1353	1026.7011
Perplexity (Llama-3.2-3B) (Human)	8,839	13.8455	12.1471	8.4284	1.0221	346.8781
Perplexity (Llama-3.2-3B) (AI)	8,839	12.8355	10.4477	16.8959	1.1205	1166.1689
Entropy (Llama-3.2-3B-Instruct) (Human)	8,839	2.6023	2.5730	0.4808	0.5658	7.6310
Entropy (Llama-3.2-3B-Instruct) (AI)	8,839	2.3347	2.3396	0.6075	0.1347	5.9743
Entropy (Llama-3.2-3B) (Human)	8,839	2.4922	2.4942	0.4534	0.0414	5.6525
Entropy (Llama-3.2-3B) (AI)	8,839	2.3794	2.3840	0.4998	0.1245	5.0878
Top-p Outliers (Llama-3.2-3B-Instruct) (Human)	8,839	0.0574	0.0545	0.0162	0.0079	0.1667
Top-p Outliers (Llama-3.2-3B-Instruct) (AI)	8,839	0.0559	0.0536	0.0186	0.0000	0.2778
Top-p Outliers (Llama-3.2-3B) (Human)	8,839	0.0427	0.0424	0.0123	0.0000	0.1282
Top-p Outliers (Llama-3.2-3B) (AI)	8,839	0.0383	0.0375	0.0156	0.0000	0.2000
Top-k Outliers (Llama-3.2-3B-Instruct) (Human)	8,839	0.1050	0.0990	0.0433	0.0037	0.4896
Top-k Outliers (Llama-3.2-3B-Instruct) (AI)	8,839	0.0896	0.0827	0.0521	0.0000	0.6429
Top-k Outliers (Llama-3.2-3B) (Human)	8,839	0.0857	0.0803	0.0388	0.0000	0.4062
Top-k Outliers (Llama-3.2-3B) (AI)	8,839	0.0776	0.0696	0.0470	0.0000	0.5714
FastDetectGPT (Llama-3.2-3B-Instruct) (Human)	8,839	-1.6820	-1.6686	1.6920	-14.0885	10.5181
FastDetectGPT (Llama-3.2-3B-Instruct) (AI)	8,839	-1.7002	-1.6766	1.7277	-11.7548	9.8134
FastDetectGPT (Llama-3.2-3B) (Human)	8,839	-0.1307	-0.0957	1.0472	-7.1757	6.8542
FastDetectGPT (Llama-3.2-3B) (AI)	8,839	0.3764	0.3362	1.5206	-11.2500	8.0566
Binoculars (Human)	8,839	0.8506	0.8608	0.1044	0.0078	1.1149
Binoculars (AI)	8,839	0.8805	0.8808	0.0767	0.0672	1.3212

Correlation Heatmap

Pearson correlation between every statistic of interest, computed over the rows where both statistics are present.

Distance Histograms

Distance Histograms per Prompt Subset

Distance Histograms per Generator Config Subset

Classifier: EditLens Roberta-Large Score

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.8623	0.2073	0.0023	0.6025	0.3427
Prompt: direct_reference	4,744	0.9045	0.3297	0.0013	0.6642	0.4954
Prompt: indirect_reference	4,384	0.8760	0.2249	0.0027	0.6111	0.3664
Prompt: revise	4,444	0.9379	0.1809	0.0032	0.5889	0.3056
❗ Prompt: rewrite	4,106	0.7209	0.0755	0.0019	0.5368	0.1401
Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.8226	0.1178	0.0034	0.5572	0.2102
Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.8214	0.2282	0.0006	0.6138	0.3715
✔️ Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.9589	0.3997	0.0023	0.6987	0.5702
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.8490	0.1604	0.0017	0.5794	0.2761
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.8617	0.1315	0.0034	0.5640	0.2318

Thresholding:

Direction: higher_is_ai
Swept for fpr_0_5pct with a found threshold of 0.8261.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: EditLens Roberta-Large Bucket

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.7646	0.5737	0.0579	0.7579	0.7032
Prompt: direct_reference	4,744	0.8109	0.6585	0.0573	0.8006	0.7676
Prompt: indirect_reference	4,384	0.7456	0.5324	0.0538	0.7393	0.6713
Prompt: revise	4,444	0.8582	0.7628	0.0594	0.8517	0.8372
❗ Prompt: rewrite	4,106	0.6297	0.3151	0.0614	0.6269	0.4579
Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.7166	0.4804	0.0550	0.7127	0.6257
Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.7258	0.4924	0.0540	0.7192	0.6369
✔️ Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.8882	0.8136	0.0673	0.8731	0.8651
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.7478	0.5407	0.0555	0.7426	0.6774
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.7475	0.5445	0.0580	0.7433	0.6796

Thresholding:

Direction: higher_is_ai
Swept for f1 with a found threshold of 0.0000.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Perplexity (Llama-3.2-3B-Instruct)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.6340	0.0753	0.0038	0.5358	0.1396
Prompt: direct_reference	4,744	0.6756	0.1290	0.0046	0.5622	0.2276
Prompt: indirect_reference	4,384	0.6976	0.1286	0.0027	0.5630	0.2274
Prompt: revise	4,444	0.6545	0.0266	0.0045	0.5110	0.0515
Prompt: rewrite	4,106	0.4962	0.0093	0.0034	0.5029	0.0183
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.4025	0.0045	0.0034	0.5006	0.0089
✔️ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.7437	0.2007	0.0034	0.5987	0.3333
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.7316	0.1494	0.0057	0.5718	0.2586
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.6305	0.0107	0.0034	0.5036	0.0210
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.6652	0.0115	0.0034	0.5040	0.0226

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 4.8037.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Perplexity (Llama-3.2-3B)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.5923	0.0001	0.0019	0.4991	0.0002
Prompt: direct_reference	4,744	0.6215	0.0000	0.0004	0.4998	0.0000
Prompt: indirect_reference	4,384	0.6632	0.0000	0.0023	0.4989	0.0000
Prompt: revise	4,444	0.6078	0.0000	0.0023	0.4989	0.0000
Prompt: rewrite	4,106	0.4671	0.0005	0.0029	0.4988	0.0010
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.3723	0.0000	0.0017	0.4992	0.0000
✔️ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.7002	0.0000	0.0028	0.4986	0.0000
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.6710	0.0000	0.0023	0.4989	0.0000
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.5857	0.0000	0.0006	0.4997	0.0000
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.6371	0.0006	0.0023	0.4991	0.0011

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 1.2354.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Entropy (Llama-3.2-3B-Instruct)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.6384	0.0815	0.0063	0.5376	0.1498
Prompt: direct_reference	4,744	0.6805	0.1336	0.0080	0.5628	0.2341
Prompt: indirect_reference	4,384	0.6961	0.1401	0.0046	0.5677	0.2447
Prompt: revise	4,444	0.6583	0.0320	0.0059	0.5131	0.0616
Prompt: rewrite	4,106	0.5081	0.0122	0.0068	0.5027	0.0239
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.4234	0.0056	0.0056	0.5000	0.0111
Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.7171	0.1804	0.0067	0.5868	0.3040
✔️ Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.7416	0.1819	0.0086	0.5867	0.3056
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.6325	0.0224	0.0050	0.5087	0.0437
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.6804	0.0172	0.0057	0.5057	0.0337

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 1.4754.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Entropy (Llama-3.2-3B)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.5758	0.0002	0.0020	0.4991	0.0005
Prompt: direct_reference	4,744	0.5843	0.0000	0.0008	0.4996	0.0000
Prompt: indirect_reference	4,384	0.6367	0.0000	0.0027	0.4986	0.0000
Prompt: revise	4,444	0.5960	0.0000	0.0018	0.4991	0.0000
Prompt: rewrite	4,106	0.4805	0.0010	0.0029	0.4990	0.0019
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.3824	0.0000	0.0011	0.4994	0.0000
Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.6629	0.0006	0.0028	0.4989	0.0011
✔️ Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.6768	0.0000	0.0029	0.4986	0.0000
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.5654	0.0000	0.0011	0.4994	0.0000
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.5961	0.0006	0.0023	0.4991	0.0011

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 0.2195.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Top-p Outliers (Llama-3.2-3B-Instruct)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.5277	0.0354	0.0081	0.5136	0.0679
Prompt: direct_reference	4,744	0.5471	0.0603	0.0072	0.5266	0.1130
Prompt: indirect_reference	4,384	0.5537	0.0511	0.0078	0.5217	0.0965
Prompt: revise	4,444	0.5169	0.0131	0.0090	0.5020	0.0255
Prompt: rewrite	4,106	0.4886	0.0141	0.0088	0.5027	0.0276
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.4706	0.0129	0.0101	0.5014	0.0252
✔️ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.6609	0.1113	0.0084	0.5514	0.1988
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.5411	0.0359	0.0057	0.5151	0.0690
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.4798	0.0090	0.0073	0.5008	0.0177
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.4865	0.0075	0.0092	0.4991	0.0147

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 0.0275.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Top-p Outliers (Llama-3.2-3B)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.6123	0.0050	0.0041	0.5005	0.0099
Prompt: direct_reference	4,744	0.6784	0.0076	0.0030	0.5023	0.0150
Prompt: indirect_reference	4,384	0.6671	0.0050	0.0050	0.5000	0.0099
Prompt: revise	4,444	0.5991	0.0032	0.0050	0.4991	0.0062
Prompt: rewrite	4,106	0.4907	0.0039	0.0034	0.5002	0.0077
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.4581	0.0034	0.0022	0.5006	0.0067
✔️ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.6949	0.0056	0.0045	0.5006	0.0111
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.6277	0.0108	0.0051	0.5029	0.0213
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.6107	0.0022	0.0028	0.4997	0.0045
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.6735	0.0029	0.0057	0.4986	0.0057

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 0.0034.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Top-k Outliers (Llama-3.2-3B-Instruct)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.6128	0.0428	0.0025	0.5201	0.0818
Prompt: direct_reference	4,744	0.6604	0.0788	0.0025	0.5382	0.1458
Prompt: indirect_reference	4,384	0.6762	0.0744	0.0014	0.5365	0.1383
Prompt: revise	4,444	0.6207	0.0095	0.0036	0.5029	0.0187
Prompt: rewrite	4,106	0.4835	0.0034	0.0024	0.5005	0.0068
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.3989	0.0011	0.0017	0.4997	0.0022
✔️ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.7201	0.1203	0.0034	0.5585	0.2141
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.6834	0.0787	0.0029	0.5379	0.1455
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.6154	0.0062	0.0022	0.5020	0.0122
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.6488	0.0075	0.0023	0.5026	0.0148

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 0.0172.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Top-k Outliers (Llama-3.2-3B)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.5792	0.0009	0.0007	0.5001	0.0018
Prompt: direct_reference	4,744	0.6190	0.0021	0.0004	0.5008	0.0042
Prompt: indirect_reference	4,384	0.6465	0.0014	0.0009	0.5002	0.0027
Prompt: revise	4,444	0.5814	0.0000	0.0009	0.4995	0.0000
Prompt: rewrite	4,106	0.4599	0.0000	0.0005	0.4998	0.0000
❗ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.3750	0.0000	0.0006	0.4997	0.0000
✔️ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.6842	0.0017	0.0000	0.5008	0.0034
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.6260	0.0023	0.0017	0.5003	0.0045
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.5830	0.0000	0.0000	0.5000	0.0000
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.6312	0.0006	0.0011	0.4997	0.0011

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of 0.0012.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: FastDetectGPT (Llama-3.2-3B-Instruct)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.4990	0.0038	0.0069	0.4985	0.0076
Prompt: direct_reference	4,744	0.5083	0.0030	0.0072	0.4979	0.0058
Prompt: indirect_reference	4,384	0.4996	0.0032	0.0100	0.4966	0.0063
Prompt: revise	4,444	0.4786	0.0041	0.0054	0.4993	0.0080
Prompt: rewrite	4,106	0.5096	0.0054	0.0049	0.5002	0.0106
Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.5026	0.0090	0.0101	0.4994	0.0176
✔️ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.6394	0.0051	0.0045	0.5003	0.0100
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.4885	0.0006	0.0068	0.4969	0.0011
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.4498	0.0017	0.0062	0.4978	0.0033
❗ Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.4121	0.0029	0.0069	0.4980	0.0057

Thresholding:

Direction: higher_is_ai
Swept for fpr_0_5pct with a found threshold of 3.3428.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: FastDetectGPT (Llama-3.2-3B)

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.3950	0.0089	0.0037	0.5026	0.0177
Prompt: direct_reference	4,744	0.3186	0.0067	0.0021	0.5023	0.0134
Prompt: indirect_reference	4,384	0.3235	0.0068	0.0055	0.5007	0.0135
Prompt: revise	4,444	0.4104	0.0095	0.0036	0.5029	0.0187
Prompt: rewrite	4,106	0.5407	0.0132	0.0039	0.5046	0.0259
✔️ Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.5726	0.0202	0.0034	0.5084	0.0395
❗ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.2700	0.0039	0.0028	0.5006	0.0078
Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.4319	0.0108	0.0040	0.5034	0.0213
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.3822	0.0062	0.0034	0.5014	0.0122
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.3175	0.0034	0.0052	0.4991	0.0068

Thresholding:

Direction: lower_is_ai
Swept for fpr_0_5pct with a found threshold of -3.1816.

Classification Histograms:

Per Prompt Subset

Per Generator Config Subset

Classifier: Binoculars

Performance:

Subset	N	AUROC	TPR	FPR	Accuracy	F1
Overall	17,678	0.6085	0.0303	0.0091	0.5106	0.0583
Prompt: direct_reference	4,744	0.6270	0.0266	0.0067	0.5099	0.0514
Prompt: indirect_reference	4,384	0.5991	0.0233	0.0105	0.5064	0.0450
Prompt: revise	4,444	0.6136	0.0275	0.0090	0.5092	0.0530
Prompt: rewrite	4,106	0.5922	0.0453	0.0102	0.5175	0.0858
Model: Hy3-NVFP4-FP8 (Temp: 0.9)	3,564	0.6375	0.0494	0.0107	0.5194	0.0932
❗ Model: Llama-4-Scout-17B-16E-Instruct-NVFP4 (Temp: 0.6)	3,558	0.5476	0.0107	0.0079	0.5014	0.0210
✔️ Model: Mixtral-8x7B-Instruct-v0.1 (Temp: 0.7)	3,508	0.6505	0.0530	0.0068	0.5231	0.1001
Model: claude-sonnet-5 (Temp: Unknown)	3,566	0.6049	0.0174	0.0079	0.5048	0.0339
Model: gpt-5.6-luna (Temp: Unknown)	3,482	0.6026	0.0213	0.0121	0.5046	0.0411