cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30334312
title: Comparison of answers to questions about tobacco cessation services in English and Spanish from different large language models

description: Introduction: Large language models (LLMs) are increasingly incorporated into digital health interventions. For example, as components of conversational agents (i.e., chatbots) for tobacco cessation. However, the multilingual reliability and consistency of these LLMs, across languages, has been underexplored in population health settings. Objective: To compare the performance of multilingual LLMs in answering user test questions related to a tobacco cessation quitline across English and Spanish within the context of a public health program. Methods: We conducted a 4×2×2 factorial design with three factors: four LLM models (ChatGPT-4o, Claude 3.5 Haiku, Gemini 2.5 Pro, and Llama 3.1-8B), two prompt languages (English or Spanish), and two question languages (English or Spanish). We compared the quality of responses generated by different models in both languages. A total of 800 responses to program-related user test questions and 400 responses to off-topic user test questions were evaluated by bilingual human reviewers using established quality assessment criteria. Mixed-effects models tested hypotheses related to linguistic congruence, model-specific performance, and interaction effects. Results: The interrater agreement across the different criteria ranged from 81.4% to 100%. The probability of correct language generation and program accuracy was 15% higher (RR = 1.15, 95% CI: 1.04–1.28; p = .006) and 0.14 points (on a 1 to 5 Likert scale) higher (β = 0.14, 95% CI: 0.06–0.23; p = .001), respectively, when the language of the question matched the language of the prompt. English-prompted LLMs presented with questions in English achieved mean Likert scores 0.36 points higher than Spanish-prompted LLMs presented with questions in Spanish (β = –0.36, 95% CI: –0.48 to –0.24; p &lt; 0.001). Model-specific differences were observed, with Llama3.1-8B and ChatGPT-4o showing the best performances under congruent conditions. Conclusions: Our findings suggest that the performance of multilingual LLMs is influenced by linguistic congruence of custom LLM prompts and LLM user questions. These findings highlight the need for language-sensitive design and evaluation to ensure equitable and effective use of LLM-based chatbots in population health intervention contexts.
DOI: 10.6084/m9.figshare.30334312.v1
title: Comparative evaluation of multilingual large language models for tobacco cessation referrals

description: Introduction: Large language models (LLMs) are increasingly incorporated into digital health interventions, including as components of conversational agents (i.e., chatbots) for tobacco cessation. However, their multilingual reliability and consistency across languages has been underexplored in population health settings. Objective: To compare the performance of multilingual LLMs in answering tobacco cessation–related questions across English and Spanish within the context of a public health program. Methods: We conducted a 4×2×2 factorial experiment evaluating four LLMs (ChatGPT-4o, Claude 3.5 Haiku, Gemini 2.5 Pro, and Llama 3.1-8B) using prompts and questions in English and Spanish. A total of 800 responses to program-related questions and 400 responses to off-topic questions were evaluated by bilingual human reviewers using established quality assessment criteria. Mixed-effects models tested hypotheses related to linguistic congruence, model-specific performance, and interaction effects. Results: Responses were of higher quality when the prompt and question languages matched. Linguistic congruence increased the probability of correct language generation (RR = 1.15, 95% CI: 1.04–1.28; p = .006) and program accuracy (β = 0.14, 95% CI: 0.06–0.23; p = .001). English-language pairs produced more complete responses than Spanish pairs (β = –0.36, 95% CI: –0.48 to –0.24; p &lt; 0.001). Model-specific differences were observed, with Llama3.1-8B and ChatGPT-4o showing the best performances under congruent conditions. Conclusions: The performance of multilingual LLMs is influenced by linguistic congruence, particularly for underrepresented languages such as Spanish. These findings highlight the need for language-sensitive design and evaluation to ensure equitable and effective use of LLM-based chatbots in population health intervention contexts.
DOI: 10.6084/m9.figshare.30334312.v2
title: Comparison of answers to questions about tobacco cessation services in English and Spanish from different large language models

description: Introduction: Large language models (LLMs) are increasingly incorporated into digital health interventions. For example, as components of conversational agents (i.e., chatbots) for tobacco cessation. However, the multilingual reliability and consistency of these LLMs, across languages, has been underexplored in population health settings. Objective: To compare the performance of multilingual LLMs in answering user test questions related to a tobacco cessation quitline across English and Spanish within the context of a public health program. Methods: We conducted a 4×2×2 factorial design with three factors: four LLM models (ChatGPT-4o, Claude 3.5 Haiku, Gemini 2.5 Pro, and Llama 3.1-8B), two prompt languages (English or Spanish), and two question languages (English or Spanish). We compared the quality of responses generated by different models in both languages. A total of 800 responses to program-related user test questions and 400 responses to off-topic user test questions were evaluated by bilingual human reviewers using established quality assessment criteria. Mixed-effects models tested hypotheses related to linguistic congruence, model-specific performance, and interaction effects. Results: The interrater agreement across the different criteria ranged from 81.4% to 100%. The probability of correct language generation and program accuracy was 15% higher (RR = 1.15, 95% CI: 1.04–1.28; p = .006) and 0.14 points (on a 1 to 5 Likert scale) higher (β = 0.14, 95% CI: 0.06–0.23; p = .001), respectively, when the language of the question matched the language of the prompt. English-prompted LLMs presented with questions in English achieved mean Likert scores 0.36 points higher than Spanish-prompted LLMs presented with questions in Spanish (β = –0.36, 95% CI: –0.48 to –0.24; p &lt; 0.001). Model-specific differences were observed, with Llama3.1-8B and ChatGPT-4o showing the best performances under congruent conditions. Conclusions: Our findings suggest that the performance of multilingual LLMs is influenced by linguistic congruence of custom LLM prompts and LLM user questions. These findings highlight the need for language-sensitive design and evaluation to ensure equitable and effective use of LLM-based chatbots in population health intervention contexts.
DOI: 10.15139/s3/lz6idl
title: Data Management and Sharing Plan for: The Human Phenotype Ontology: Accelerating Computational Integration of Clinical Data for Genomics

description: The Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data.
description: Data Management and Sharing Plan
DOI: 10.6084/m9.figshare.31325891
title: Integrating morphology and phylogenetics reveals new species, records, and provides an updated checklist of Trichiaceae in China

description: The Trichiaceae, a major family of Myxomycetes, has undergone significant taxonomic revision in recent years. Yet, systematic research on this group in China remains limited, resulting in outdated taxonomy and persistent gaps in species diversity and biogeographic understanding. To resolve this, this study performed a comprehensive revision of Chinese Trichiaceae, combining morphological analysis (light and scanning electron microscopy) and multigene phylogenetics (nuclear 18S rDNA, elongation factor-1 alpha, and mitochondrial small subunit ribosomal RNA) based on specimens deposited in the Herbarium of Fungi at Nanjing Normal University and the Herbarium Mycologicum, Academiae Sinicae. We also synthesized published literature to compile an updated checklist of 65 species with detailed Chinese distribution records. This study describes two new species (<i>Metatrichia scintillans</i> and <i>Trichia coronata</i>), revises one species (<i>Oligonema latitubulare</i>), and reports four new records for China (<i>Ophiotheca calongei, Trichia acetocorticola, Trichia pinicola</i>, and <i>Trichia taeniifila</i>). This study addresses key knowledge gaps in China’s myxomycete biota and provides a standardized framework for future research on Trichiaceae biodiversity and taxonomy.
DOI: 10.6084/m9.figshare.31325891.v1
title: Integrating morphology and phylogenetics reveals new species, records, and provides an updated checklist of Trichiaceae in China

description: The Trichiaceae, a major family of Myxomycetes, has undergone significant taxonomic revision in recent years. Yet, systematic research on this group in China remains limited, resulting in outdated taxonomy and persistent gaps in species diversity and biogeographic understanding. To resolve this, this study performed a comprehensive revision of Chinese Trichiaceae, combining morphological analysis (light and scanning electron microscopy) and multigene phylogenetics (nuclear 18S rDNA, elongation factor-1 alpha, and mitochondrial small subunit ribosomal RNA) based on specimens deposited in the Herbarium of Fungi at Nanjing Normal University and the Herbarium Mycologicum, Academiae Sinicae. We also synthesized published literature to compile an updated checklist of 65 species with detailed Chinese distribution records. This study describes two new species (<i>Metatrichia scintillans</i> and <i>Trichia coronata</i>), revises one species (<i>Oligonema latitubulare</i>), and reports four new records for China (<i>Ophiotheca calongei, Trichia acetocorticola, Trichia pinicola</i>, and <i>Trichia taeniifila</i>). This study addresses key knowledge gaps in China’s myxomycete biota and provides a standardized framework for future research on Trichiaceae biodiversity and taxonomy.
DOI: 10.7910/dvn/wfnfyi
title: PED-2025

description: Processed HOBO environmental data for 2025.
DOI: 10.5281/zenodo.18624432
title: weecology/PortalData: 6.53.0

description: v6.53.0
DOI: 10.5517/ccdc.csd.cc2kvrfm
title: CCDC 2379201: Experimental Crystal Structure Determination

description: Related Article: Astam Mandal, Rukhsar Bano, Soumya Chattopadhyay, Rana Banerjee, Dipanti Borah, Naitik Gupta, Maheswaran Shanmugam, Debabrata Maiti|2026|Angew.Chem.,Int.Ed.|65|e23983|doi:10.1002/anie.202523983
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kvrgn
title: CCDC 2379202: Experimental Crystal Structure Determination

description: Related Article: Astam Mandal, Rukhsar Bano, Soumya Chattopadhyay, Rana Banerjee, Dipanti Borah, Naitik Gupta, Maheswaran Shanmugam, Debabrata Maiti|2026|Angew.Chem.,Int.Ed.|65|e23983|doi:10.1002/anie.202523983
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l0kt0
title: CCDC 2383832: Experimental Crystal Structure Determination

description: Related Article: Cheng Pan, Hamza Khan, Xiaoting Liu, Limin Wang, Jianwei Han|2026|Org.Lett.|||doi:10.1021/acs.orglett.5c05448
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l0ky4
title: CCDC 2383836: Experimental Crystal Structure Determination

description: Related Article: Cheng Pan, Hamza Khan, Xiaoting Liu, Limin Wang, Jianwei Han|2026|Org.Lett.|||doi:10.1021/acs.orglett.5c05448
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2lm17j
title: CCDC 2401577: Experimental Crystal Structure Determination

description: Related Article: Youhai Liu, Sitong Chen, Tianyu Jiang, Fusheng Yang, Wenlong Yin, Guoyang Yu, Yanqiang Yang, Wenquan Zhang|2026|Chem.Eng.Journal|530||doi:10.1016/j.cej.2026.173727
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2lr76t
title: CCDC 2405606: Experimental Crystal Structure Determination

description: Related Article: Usha Yadav, Sanoop P. Chandrasekharan, Anamika Dhami, Kishor Mohanan|2026|Org.Lett.|||doi:10.1021/acs.orglett.6c00097
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2m0dqs
title: CCDC 2413465: Experimental Crystal Structure Determination

description: Related Article: Shuo Song, Jiacheng Wu, Ruobin Wang, Zhongxian Li, Anxiang Huang, Jun Zhu|2026|Angew.Chem.,Int.Ed.|65|e17311|doi:10.1002/anie.202517311
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2n6pxh
title: CCDC 2449307: Experimental Crystal Structure Determination

description: Related Article: Yunming Liu, Linlin Chen, Xiangdi Huang, Peng Liu, Zhigang Ma, Yanxiong Liu, Yuchen Zhang, Liyan Zheng, Qiue Cao|2026|Adv.Funct.Mater.|36|e14361|doi:10.1002/adfm.202514361
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2n6pzk
title: CCDC 2449309: Experimental Crystal Structure Determination

description: Related Article: Yunming Liu, Linlin Chen, Xiangdi Huang, Peng Liu, Zhigang Ma, Yanxiong Liu, Yuchen Zhang, Liyan Zheng, Qiue Cao|2026|Adv.Funct.Mater.|36|e14361|doi:10.1002/adfm.202514361
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2n7by6
title: CCDC 2449928: Experimental Crystal Structure Determination

description: Related Article: Ryan M. Hacker, Jacob J. Smith, David C. Platt, Maria I. Loughlin, Emma N. Grabowski, William W. Brennessel, Marjorie A. Jones, Michael I. Webb|2026|RSC Advances|16|7056|doi:10.1039/d5ra08313c
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pm8l6
title: CCDC 2491178: Experimental Crystal Structure Determination

description: Related Article: Astam Mandal, Rukhsar Bano, Soumya Chattopadhyay, Rana Banerjee, Dipanti Borah, Naitik Gupta, Maheswaran Shanmugam, Debabrata Maiti|2026|Angew.Chem.,Int.Ed.|65|e23983|doi:10.1002/anie.202523983
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pry2h
title: CCDC 2495657: Experimental Crystal Structure Determination

description: Related Article: Naoya Kinoshita, Nanami Kotani, Masaya Sugiura, Kotaro Matsumura, Daisuke Sakamaki, Daiki Tauchi, Masashi Hasegawa, Hidetoshi Kawai, Yoshitaka Tsuchido|2026|Angew.Chem.,Int.Ed.|65|e25108|doi:10.1002/anie.202525108
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2q2xk9
title: CCDC 2505251: Experimental Crystal Structure Determination

description: Related Article: Silas C. Eiden, Erik Misselwitz, John Bergner, Frank Rominger, Milan Kivala
|2026|Helv.Chim.Acta||e00227|doi:10.1002/hlca.202500227
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2q2xmc
title: CCDC 2505253: Experimental Crystal Structure Determination

description: Related Article: Silas C. Eiden, Erik Misselwitz, John Bergner, Frank Rominger, Milan Kivala
|2026|Helv.Chim.Acta||e00227|doi:10.1002/hlca.202500227
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2q2xnd
title: CCDC 2505254: Experimental Crystal Structure Determination

description: Related Article: Silas C. Eiden, Erik Misselwitz, John Bergner, Frank Rominger, Milan Kivala
|2026|Helv.Chim.Acta||e00227|doi:10.1002/hlca.202500227
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2q2xrh
title: CCDC 2505257: Experimental Crystal Structure Determination

description: Related Article: Silas C. Eiden, Erik Misselwitz, John Bergner, Frank Rominger, Milan Kivala
|2026|Helv.Chim.Acta||e00227|doi:10.1002/hlca.202500227
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2q2xh7
title: CCDC 2505249: Experimental Crystal Structure Determination

description: Related Article: Silas C. Eiden, Erik Misselwitz, John Bergner, Frank Rominger, Milan Kivala
|2026|Helv.Chim.Acta||e00227|doi:10.1002/hlca.202500227
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2qvthx
title: CCDC 2528220: Experimental Crystal Structure Determination

description: Related Article: Muhammad Shoaib Akhtar, Asmara Ismail, Shahzad Murtaz*, Muhammad Nawaz Tahir, Saima Shamim, Usman Ali Rana|2016|J.Chem.Soc.Pak.|38|242|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pk44k
title: CCDC 2489118: Experimental Crystal Structure Determination

description: Related Article: Miguel Gallardo, Roberto Sánchez, Rodrigo Arancibia, David Villaman, Patricia M. Toro-Sánchez, Elizabeth Navarrete, Pilar Morales, Carolina Mascayano|2026|Polyhedron|289||doi:10.1016/j.poly.2026.118017
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pk45l
title: CCDC 2489119: Experimental Crystal Structure Determination

description: Related Article: Miguel Gallardo, Roberto Sánchez, Rodrigo Arancibia, David Villaman, Patricia M. Toro-Sánchez, Elizabeth Navarrete, Pilar Morales, Carolina Mascayano|2026|Polyhedron|289||doi:10.1016/j.poly.2026.118017
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.