cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.27203
title: A dataset for marking the ship faults field.
title: 船舶故障领域标注数据集

description: We collected 1,347 text corpora in the field of ship faults and used the BIO sequence labeling method for data labeling. Among them, the faulty equipment was marked as E, the fault phenomenon as P, the fault cause as R, and the fault measure as M. Finally, 1,389 faulty equipment entities, 1,538 faulty phenomenon entities, 1,457 faulty cause entities and 1,526 faulty measure entities were obtained.
description: We collected 1,347 text corpora in the field of ship faults and used the BIO sequence labeling method for data labeling. Among them, the faulty equipment was marked as E, the fault phenomenon as P, the fault cause as R, and the fault measure as M. Finally, 1,389 faulty equipment entities, 1,538 faulty phenomenon entities, 1,457 faulty cause entities and 1,526 faulty measure entities were obtained.
DOI: 10.57760/sciencedb.j00133.00560
title: Research on Multi-Institution Data Fusion Methods Based on Cloud-Edge Collaboration and Federated Learning
title: 基于云边协作和联邦学习的多机构数据融合方法研究

description: Set up independent identically distributed scenarios and low, medium, and high heterogeneity non independent identically distributed scenarios on the MNIST, CIFAR-10, and CIFAR-100 datasets to test the performance of the model in various complex scenarios. Including CEFDFM-MI model code, experimental data, and baseline model. 
description: Set up independent identically distributed scenarios and low, medium, and high heterogeneity non independent identically distributed scenarios on the MNIST, CIFAR-10, and CIFAR-100 datasets to test the performance of the model in various complex scenarios. Including CEFDFM-MI model code, experimental data, and baseline model.
DOI: 10.57760/sciencedb.j00133.00575
title: Experimental data set in the field of new energy vehicles
title: 新能源汽车领域实验数据集

description: 该数据集包括本文实验的所有原始数据以及论文中呈现的图表。具体来说，数据集包括：新能源汽车专利数据。xlsx，新能源汽车论文数据。xlsx，新能源汽车政策数据。xlsx，电状态信息数据。xlsx，和 DCD 审查数据。xlsx。图数据：图 1-4 为 pptx 格式，图 5、6、11-14 为 Python 输出的 PNG 格式，图 7-10 为 Gephi 输出的 PDF 格式共现网络图。
description: 该数据集包括本文实验的所有原始数据以及论文中呈现的图表。具体来说，数据集包括：新能源汽车专利数据。xlsx，新能源汽车论文数据。xlsx，新能源汽车政策数据。xlsx，电状态信息数据。xlsx，和 DCD 审查数据。xlsx。图数据：图 1-4 为 pptx 格式，图 5、6、11-14 为 Python 输出的 PNG 格式，图 7-10 为 Gephi 输出的 PDF 格式共现网络图。
DOI: 10.57760/sciencedb.j00133.00573
title: A dataset for the configuration research on the influencing factors of online medical team performance
title: 在线医疗团队绩效的影响因素构型研究数据集

description: This dataset contains three CSV files, which respectively support the main analysis of the paper (one) and the dynamic analysis (two).
description: This dataset contains three CSV files, which respectively support the main analysis of the paper (one) and the dynamic analysis (two).
DOI: 10.57760/sciencedb.28947
title: Dataset for the Multi-Class Classification of Research Gap Sentences
title: 研究空缺句分类数据集

description: We sample the odd-numbered papers (excluding review articles and posters) from the proceedings published by IJCAI, ICML, and ACL in 2021, selecting the abstract and introduction sections as the original corpus for manual annotation of research gap sentences. The syntactic complexity indices of each research gap sentence are then calculated using L2SCA and Coh-Metrix.
description: We sample the odd-numbered papers (excluding review articles and posters) from the proceedings published by IJCAI, ICML, and ACL in 2021, selecting the abstract and introduction sections as the original corpus for manual annotation of research gap sentences. The syntactic complexity indices of each research gap sentence are then calculated using L2SCA and Coh-Metrix.
DOI: 10.57760/sciencedb.28877
title: XAI-InfoAdopt Dataset
title: 可解释人工智能内容关联度与信息采纳数据集

description: The dataset contains two parallel experimental results, corresponding to two types of real-life task scenarios: medical information consultation and life information consultation. The experiment set up four experimental condition groups (no explanation group, low correlation explanation group, medium correlation explanation group, high correlation explanation group), and collected effective samples N=300 for each experiment. The data included participants' perceived consensus and willingness to adopt AI explanations under different conditions. 
description: The dataset contains two parallel experimental results, corresponding to two types of real-life task scenarios: medical information consultation and life information consultation. The experiment set up four experimental condition groups (no explanation group, low correlation explanation group, medium correlation explanation group, high correlation explanation group), and collected effective samples N=300 for each experiment. The data included participants' perceived consensus and willingness to adopt AI explanations under different conditions.
DOI: 10.57760/sciencedb.j00133.00568
title: The data after experimental preprocessing
title: 实验预处理后的数据

description: Preprocessed experimental data of the paper "Research on the Construction of Cognitive Graph and Generation of Vector Knowledge Base in the Medical Field", including knowledge graphs, knowledge graph term matrices, entity-attribute classification relationships, and results of concept indexing and entity extraction.
description: Preprocessed experimental data of the paper "Research on the Construction of Cognitive Graph and Generation of Vector Knowledge Base in the Medical Field", including knowledge graphs, knowledge graph term matrices, entity-attribute classification relationships, and results of concept indexing and entity extraction.
DOI: 10.57760/sciencedb.j00133.00567
title: BibSQL Dataset
title: BibSQL数据集

description: BibSQL, the first Text-to-SQL dataset in the Chinese book retrieval scenario, uses a node combination strategy to generate diverse query questions and simulate real retrieval requirements.
description: BibSQL, the first Text-to-SQL dataset in the Chinese book retrieval scenario, uses a node combination strategy to generate diverse query questions and simulate real retrieval requirements.
DOI: 10.57760/sciencedb.j00133.00565
title: Dataset of Traditional Chinese Medicine Knowledge Q&A
title: 中医知识问答数据集

description: This study selects classic Chinese medicine literature as the data source for constructing Chinese medicine question-answer knowledge pairs, and the dataset contains 6,157 question-answer knowledge pairs.
description: This study selects classic Chinese medicine literature as the data source for constructing Chinese medicine question-answer knowledge pairs, and the dataset contains 6,157 question-answer knowledge pairs.
DOI: 10.17026/ar/waizjm
title: PAN-00179754 - pendant with triangular loop

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00179754&lt;/p&gt;
description: Modified: 2025-09-17T09:20:41+02:00
DOI: 10.57760/sciencedb.j00133.00564
title: Social media rumor detection dataset
title: 社交媒体谣言检测数据集

description: The social media rumor detection dataset includes two datasets: Twitter and Weibo. The Twitter dataset was published for MediaEval2016 to validate multimedia usage tasks. The Twitter dataset consists of 17 events, including textual content, additional images/videos, and other social environment information. The rumors in the Weibo dataset were verified by Weibo's official rumor debunking system as fake posts between May 2012 and January 2016. The non rumors in the dataset were collected from Xinhua News Agency, which is an authoritative news source in China. 
description: The social media rumor detection dataset includes two datasets: Twitter and Weibo. The Twitter dataset was published for MediaEval2016 to validate multimedia usage tasks. The Twitter dataset consists of 17 events, including textual content, additional images/videos, and other social environment information. The rumors in the Weibo dataset were verified by Weibo's official rumor debunking system as fake posts between May 2012 and January 2016. The non rumors in the dataset were collected from Xinhua News Agency, which is an authoritative news source in China.
DOI: 10.57760/sciencedb.27530
title: 科学论文颠覆性数据
title: 科学论文颠覆性数据

description: 本数据集为论文开展实证分析使用的原始数据，共有20列和396070行。 每一行为单篇论文的相关信息。具体来说，doi为论文的doi号，doc_type_id为文献类型，pub_year为论文发表年份，is_open_access为论文是否开放获取，n_pages为论文页数，n_refs为参考文献数量，n_cits为论文被论文引用次数，title为论文标题，n_keyword为论文关键词数量，JIF为期刊影响因子，n_authors为作者数量，n_subject_category为学科领域数量，IPC_num为施引专利去重前四位IPC号个数，disruption为论文颠覆性指数，pat_cit_num为施引专利数量，patent_cit为论文是否被专利引用，tec_time_lag为技术界时滞性，tec_time_last为技术界持续性，sci_time_last为科学界持续性，sci_time_lag为科学界时滞性。 对于被引次数等累积指标，本数据集统计时间为2023年11月，与现有情况可能存在一定出入。
description: 本数据集为论文开展实证分析使用的原始数据，共有20列和396070行。 每一行为单篇论文的相关信息。具体来说，doi为论文的doi号，doc_type_id为文献类型，pub_year为论文发表年份，is_open_access为论文是否开放获取，n_pages为论文页数，n_refs为参考文献数量，n_cits为论文被论文引用次数，title为论文标题，n_keyword为论文关键词数量，JIF为期刊影响因子，n_authors为作者数量，n_subject_category为学科领域数量，IPC_num为施引专利去重前四位IPC号个数，disruption为论文颠覆性指数，pat_cit_num为施引专利数量，patent_cit为论文是否被专利引用，tec_time_lag为技术界时滞性，tec_time_last为技术界持续性，sci_time_last为科学界持续性，sci_time_lag为科学界时滞性。 对于被引次数等累积指标，本数据集统计时间为2023年11月，与现有情况可能存在一定出入。
DOI: 10.57760/sciencedb.j00133.00562
title: The data sampling and processing code used in the AEIM method.
title: The data sampling and processing code used in the AEIM method.

description: The data sampling and processing code used in the AEIM method.
description: The data sampling and processing code used in the AEIM method.
DOI: 10.34856/eos-rs_202510_vietnam_north_central_typhoon_bualoi_floods
title: EOS-RS Damage Proxy Map: North Central, Vietnam, Floods, 01 Oct 2025

description: The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Damage Proxy Map (DPM) depicting areas that are likely damaged in North Central, Vietnam, due to typhoon Bualoi. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (27 Jul 2025 to 25 Sep 2025) and after (01 Oct 2025) the event.
DOI: 10.57760/sciencedb.27118
title: 水稻分子育种科技文献图谱式摘要生成实验数据集
title: 水稻分子育种科技文献图谱式摘要生成实验数据集

description: 本数据集包含了：水稻分子育种科技文献图谱式摘要生成实验的元数据清单、训练和测试数据、不同提示词在各温度下的实验结果数据、本研究生成的各论文的图谱摘要数据文件、生成摘要的人工评测结果数据、本研究对qwen2.5-7B-Instruct微调和使用GraphRAG的参数数据文件、本研究的最终结果数据、基线模型LightRAG的实验结果数据、对比模型LEAD-3、BERT、BART和DeepSeek的实验结果数据、消融实验中提示词、微调和GraphRAG的实验结果数据。
description: 本数据集包含了：水稻分子育种科技文献图谱式摘要生成实验的元数据清单、训练和测试数据、不同提示词在各温度下的实验结果数据、本研究生成的各论文的图谱摘要数据文件、生成摘要的人工评测结果数据、本研究对qwen2.5-7B-Instruct微调和使用GraphRAG的参数数据文件、本研究的最终结果数据、基线模型LightRAG的实验结果数据、对比模型LEAD-3、BERT、BART和DeepSeek的实验结果数据、消融实验中提示词、微调和GraphRAG的实验结果数据。
DOI: 10.57760/sciencedb.j00133.00558
title: Time series prediction method supporting data using convex hull knowledge distillation technology.
title: 引入凸包知识蒸馏技术的时间序列预测方法支撑数据

description: The data includes KDConv model training scripts, experimental configuration files, prediction result files, and raw evaluation data to ensure that all experiments are reproducible and the results are verifiable The dataset used in this paper's experiment is: ① ETT (Electric Transformer Temperature): divided into hourly level dataset (ETTh) and 15 minute level dataset (ETTm), which records the load characteristics of seven types of oil immersed and power transformers from July 2016 to July 2018. ② Exchange_rate: This dataset collects daily exchange rate information for 8 countries from 1990 to 2016. ③ Weather: Contains 21 weather indicators such as air temperature and humidity, collected in 2020 and recorded every 10 minutes. ④ Electricity: 321 customers' hourly electricity consumption was collected from 2012 to 2014. ⑤ Traffic: describes the road occupancy rate. It contains hourly data recorded by sensors on San Francisco highways from 2015 to 2016. It should be noted that the training/testing set partitioning of all datasets in this experiment adopts a time continuous segmentation strategy, without artificially introducing distribution mutations. Therefore, the main purpose is to verify the effectiveness of the method under stable distributions 
description: The data includes KDConv model training scripts, experimental configuration files, prediction result files, and raw evaluation data to ensure that all experiments are reproducible and the results are verifiable The dataset used in this paper's experiment is: ① ETT (Electric Transformer Temperature): divided into hourly level dataset (ETTh) and 15 minute level dataset (ETTm), which records the load characteristics of seven types of oil immersed and power transformers from July 2016 to July 2018. ② Exchange_rate: This dataset collects daily exchange rate information for 8 countries from 1990 to 2016. ③ Weather: Contains 21 weather indicators such as air temperature and humidity, collected in 2020 and recorded every 10 minutes. ④ Electricity: 321 customers' hourly electricity consumption was collected from 2012 to 2014. ⑤ Traffic: describes the road occupancy rate. It contains hourly data recorded by sensors on San Francisco highways from 2015 to 2016. It should be noted that the training/testing set partitioning of all datasets in this experiment adopts a time continuous segmentation strategy, without artificially introducing distribution mutations. Therefore, the main purpose is to verify the effectiveness of the method under stable distributions
DOI: 10.57760/sciencedb.j00133.00554
title: Shenzhen Government Similar Question Retrieval Training and Test Sets
title: 深圳市政务相似问题检索训练集和测试集

description: This dataset is sourced from the interactive consultation section of the "Shenzhen Government Online" website. Each consultation entry includes information such as the question topic, detailed content, and corresponding responses. In the training set, based on the original crawled questions qi and their respective answers ai, PromptT is utilized to generate semantically positive samples (similar questions) qi+ and hard negative samples (dissimilar questions) qN-, forming the complete triplet data (qi , qi+, qi-) required for contrastive training. Incorporating answer information provides additional contextual background knowledge for the LLM, simultaneously bridging the semantic gap between different questions sharing identical answers. In the test set, rather than using triplet data, the dataset focuses on generating question pairs (qi , qi') that exhibit stricter semantic equivalence. This approach aims to simulate realistic scenarios encountered in similar question retrieval tasks. To achieve this, PromptS is designed to create qi' through a rewriting task based on the original question qi. Compared to directly using the original question-similar question pairs (qi , qi+) from the training set as test data, this new data generation strategy significantly reduces bias toward LLM-generated pseudo-data, thereby enhancing the fairness and credibility of the evaluation.
description: This dataset is sourced from the interactive consultation section of the "Shenzhen Government Online" website. Each consultation entry includes information such as the question topic, detailed content, and corresponding responses. In the training set, based on the original crawled questions qi and their respective answers ai, PromptT is utilized to generate semantically positive samples (similar questions) qi+ and hard negative samples (dissimilar questions) qN-, forming the complete triplet data (qi , qi+, qi-) required for contrastive training. Incorporating answer information provides additional contextual background knowledge for the LLM, simultaneously bridging the semantic gap between different questions sharing identical answers. In the test set, rather than using triplet data, the dataset focuses on generating question pairs (qi , qi') that exhibit stricter semantic equivalence. This approach aims to simulate realistic scenarios encountered in similar question retrieval tasks. To achieve this, PromptS is designed to create qi' through a rewriting task based on the original question qi. Compared to directly using the original question-similar question pairs (qi , qi+) from the training set as test data, this new data generation strategy significantly reduces bias toward LLM-generated pseudo-data, thereby enhancing the fairness and credibility of the evaluation.
DOI: 10.57760/sciencedb.26306
title: DBLP数据集2010-2015年知识图谱
title: DBLP数据集2010-2015年知识图谱

description: 为全面刻画学术实体及其交互，本数据集在构建知识图谱时将论文、作者、发表场所（会议或期刊）及概念（研究主题或关键词）视为实体，并定义了四种单向关联：撰写关系（WrittenBy），用于表示论文与作者的对应，例如（Paper1, WrittenBy, Author1）；地点关联关系（PublishedAt），用于反映论文与发布场所的隶属，例如（Paper1, PublishedAt, Venue1）；引用关系（CitedBy），用于描述论文间的引用，例如（Paper1, CitedBy, Paper2）；主题关系（HasConcept），用于刻画论文与研究概念的关联，例如（Paper1, HasConcept, Concept1）。
description: 为全面刻画学术实体及其交互，本数据集在构建知识图谱时将论文、作者、发表场所（会议或期刊）及概念（研究主题或关键词）视为实体，并定义了四种单向关联：撰写关系（WrittenBy），用于表示论文与作者的对应，例如（Paper1, WrittenBy, Author1）；地点关联关系（PublishedAt），用于反映论文与发布场所的隶属，例如（Paper1, PublishedAt, Venue1）；引用关系（CitedBy），用于描述论文间的引用，例如（Paper1, CitedBy, Paper2）；主题关系（HasConcept），用于刻画论文与研究概念的关联，例如（Paper1, HasConcept, Concept1）。
DOI: 10.57760/sciencedb.j00133.00472
title: Preprocessing dataset for institution name alignment
title: 机构名称对齐预处理数据集

description: The preprocessed dataset obtained from the "Name Standardization Database Construction" special task project， includes 23240 records、involving unique identifier (UUID), preferred name, standardized name, and planned GRID IDs fields
description: The preprocessed dataset obtained from the "Name Standardization Database Construction" special task project， includes 23240 records、involving unique identifier (UUID), preferred name, standardized name, and planned GRID IDs fields
DOI: 10.57760/sciencedb.25634
title: The named entity recognition dataset of the Book of the Later Han
title: 《后汉书》命名实体识别数据集

description: The named entity recognition dataset of the Book of the Later Han
description: The named entity recognition dataset of the Book of the Later Han
DOI: 10.5281/zenodo.17787517
title: (CPSD) Predicción exacta de la constante de estructura fina desde la entropía máxima de entrelazamiento a escala de Planck en Critical Planckian Spin Dynamic

description: Utilizando exclusivamente el principio físico de máxima entropía de entrelazamiento de von Neumannalaescala de Planck —sin introducir en ningún momento datos experimentales de la constante de estructura fina ni de la electrodinámica cuántica— la extrapolación de escalamiento de tamaño finito en redes críticas de espines planckianos de hasta tamaño 484 determina de forma única e independiente el exponente crítico universal εc(∞) = 0,46788017(1). La geometría fractal del punto fijo ultravioleta del modelo Critical Planckian Spin Dynamics (CPSD) genera una corrección crítica no perturbativa completamente calculable δα−1 crit = 64π3 (ln L∗)2 sin4 π L∗ εc(∞), L∗ =2(4+εc) = 9,34376034, que, al sumarse a la contribución estándar conocida de QED evaluada a baja energía, predice α−1 = 137,035999046 ±0,000000016teór. Este valor coincide con la determinación experimental CODATA 2024 dentro de una parte en 6 ×109. En este trabajo se presenta la derivación completa, explícita y paso a paso de cada uno de los factores de la fórmula anterior. La constante de estructura fina no es un parámetro libre de la Naturaleza: es un fenómeno crítico del espacio-tiempo cuántico
DOI: 10.5281/zenodo.17787518
title: (CPSD) Predicción exacta de la constante de estructura fina desde la entropía máxima de entrelazamiento a escala de Planck en Critical Planckian Spin Dynamic

description: Utilizando exclusivamente el principio físico de máxima entropía de entrelazamiento de von Neumannalaescala de Planck —sin introducir en ningún momento datos experimentales de la constante de estructura fina ni de la electrodinámica cuántica— la extrapolación de escalamiento de tamaño finito en redes críticas de espines planckianos de hasta tamaño 484 determina de forma única e independiente el exponente crítico universal εc(∞) = 0,46788017(1). La geometría fractal del punto fijo ultravioleta del modelo Critical Planckian Spin Dynamics (CPSD) genera una corrección crítica no perturbativa completamente calculable δα−1 crit = 64π3 (ln L∗)2 sin4 π L∗ εc(∞), L∗ =2(4+εc) = 9,34376034, que, al sumarse a la contribución estándar conocida de QED evaluada a baja energía, predice α−1 = 137,035999046 ±0,000000016teór. Este valor coincide con la determinación experimental CODATA 2024 dentro de una parte en 6 ×109. En este trabajo se presenta la derivación completa, explícita y paso a paso de cada uno de los factores de la fórmula anterior. La constante de estructura fina no es un parámetro libre de la Naturaleza: es un fenómeno crítico del espacio-tiempo cuántico
DOI: 10.57760/sciencedb.25633
title: A dataset of classical Chinese texts and abstracts from the Book of Han, Book of the Later Han, and Records of the Three Kingdoms.
title: 《汉书》、《后汉书》、《三国志》文言文-摘要数据集

description: A dataset of classical Chinese texts and abstracts from the Book of Han, Book of the Later Han, and Records of the Three Kingdoms.
description: A dataset of classical Chinese texts and abstracts from the Book of Han, Book of the Later Han, and Records of the Three Kingdoms.
DOI: 10.34740/kaggle/dsv/13956106
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.57760/sciencedb.20062
title: Research on the impact of AI medical voice assistant voice characteristics on older adults' perceived credibility and intention to use
title: The impact of AI medical voice assistants

description: The experiment recruited 180 elderly people to examine the impact of voice gender and communication style of AI medical voice assistants on the perceived credibility of elderly people in real medical environments. This study conducted a 3 (voice gender: female/male/non binary) × 2 (communication mode: expert/partner) inter subject experiment to examine the effects of voice gender and communication mode of artificial intelligence medical voice assistants on the perceived credibility and willingness of elderly people, as well as the mechanism of the stereotype dimensions of perceived warmth and perceived professionalism. 
description: The experiment recruited 180 elderly people to examine the impact of voice gender and communication style of AI medical voice assistants on the perceived credibility of elderly people in real medical environments. This study conducted a 3 (voice gender: female/male/non binary) × 2 (communication mode: expert/partner) inter subject experiment to examine the effects of voice gender and communication mode of artificial intelligence medical voice assistants on the perceived credibility and willingness of elderly people, as well as the mechanism of the stereotype dimensions of perceived warmth and perceived professionalism.
DOI: 10.57760/sciencedb.j00133.00551
title: WikiRE1.0
title: 百科数据集1.0

description: A Wikipedia text–triple QA dataset, which is collected from randomly sampled entries of Baidu Baike and Wikipedia in various fields. For those particularly short entries, GPT-4 is used to expand and merge the short texts. The Infobox of the encyclopedia entries is used as the basis for the triple answers. GPT-4 is also used to generate more triples by supplementing the entry text paragraphs. The triples are then manually adjusted to obtain the Wikipedia text–triple QA dataset named WikiRE1.0.
description: A Wikipedia text–triple QA dataset, which is collected from randomly sampled entries of Baidu Baike and Wikipedia in various fields. For those particularly short entries, GPT-4 is used to expand and merge the short texts. The Infobox of the encyclopedia entries is used as the basis for the triple answers. GPT-4 is also used to generate more triples by supplementing the entry text paragraphs. The triples are then manually adjusted to obtain the Wikipedia text–triple QA dataset named WikiRE1.0.
DOI: 10.57760/sciencedb.j00133.00549
title: Social robot recognition dataset
title: 社交机器人识别数据集

description: This dataset is a social robot recognition dataset. It is mainly used for the testing of social robot recognition models.
description: This dataset is a social robot recognition dataset. It is mainly used for the testing of social robot recognition models.