cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57982/3eh6-ag63
title: Immunogenicity, Safety, Tolerability, and Behavioral Consequences of an HPV-6, -11, -16, -18 Vaccine in HIV-Infected Young Women 

description: A Phase II, open-label, multi-center study that evaluated the immunogenicity, safety, tolerability, and behavioral impact of an HPV-6, -11, -16, -18 vaccine in HIV-infected young women. The vaccine was administered at the recommended dose and schedule (Day 0, Week 8, and Week 24) with safety assessments after each vaccination and reactive antibody measurements pre- and post-vaccination. Attitudes and behaviors were measured using self-administered questionnaires.
DOI: 10.57982/kdwt-be60
title: PHASES: Provision of HIV Treatment at ATN Sites: An Evaluation for Stakeholders

description: An observational study examining the proportion of youth at Adolescent Medicine Trials Units (AMTUs) engaged in care, prescribed antiretroviral therapy (ART), and attained viral suppression per subject year. Psychosocial and risk-taking behavioral data of study subjects were collected using an Audio Computer-Assisted Self-Interview (ACASI) at study entry. Biomedical, antiretroviral therapy, and healthcare utilization information of study subjects was abstracted through retrospective and prospective medical record reviews covering a total maximum of 24 months per subject. Data on missed visits and other healthcare services utilization were abstracted from electronic appointment systems or other electronic systems at clinical sites. Data were also collected from each AMTU to assess clinic level variables at baseline (within 30 days of protocol registration) and 48 and 96 weeks after baseline.
DOI: 10.57982/v5av-dn69
title: Collaborative Home Infant Monitoring Evaluation

description: Infants were enrolled into four groups: healthy term, preterm infants <1750g w/o significant morbidity, sibling of SIDS, and babies experiencing apparent life-threatening events. Objectives were to: determine monitor efficacy in identifying episodes endangering the infant's health; determine conditions optimizing use of apnea monitors in high risk infants; correlate physiological markers with the propensity for life-threatening events; and report on maturation of heart and respiratory function in sleeping infants. Data were collected from nightly home recordings (via CHIME Monitor device) and one sleep lab polysomnography (PSG) session (via CHIME Monitor and ALICE3 devices). CRF data include sociodemographic and medical information on mother and infant at entry and from scheduled medical follow-up visits through 1-year of age, weekly phone calls, monitor knowledge and satisfaction scales, periodic assessments with the Bayley II, NCAST, subscales of the Parenting Stress Index, and hospitalizations.
DOI: 10.57982/rf12-me68
title: Identity Development in Gay/Bisexual/Questioning Male Youth: Implications for HIV Sexual Risk

description: A cross-sectional, three phase study which examined the relationship among ethnic, gay, masculine, and ego identities, and conflicts or difficulties faced by GBQ male youth working to integrate these identities. Phase I involved surveying GBQ male adolescents with quantitative measures and using this information to create a stratified purposive sample for Phase II. Phase II involved conducting in-depth individual qualitative interviews with a sub-sample of GBQ youth from Phase I, as well as individual and focus group validation check interviews with GBQ youth and adult experts. Phase III involved conducting focus groups with GBQ youth to develop the components of an HIV prevention intervention.
DOI: 10.3886/e135481v1
title: Data and Code for: Does Advisor Gender Affect Women's Persistence in Economics?

description: Women persist in the field of economics at significantly lower rates than men. We show that the gender of an academic advisor is an important determinant of female undergraduates' persistence in economics. We use data from a 4-year college where first-year economics majors are randomly assigned to advisors who are also faculty members in the economics department. Advisors help students choose courses and monitor their academic progress. We find that having a female rather than a male advisor reduces female students' first-year dropout rates and increases their likelihood of graduating with an economics degree.
description: First-time enrolling university students at the American University of Beirut. Smallest Geographic Unit: Lebanon
DOI: 10.3886/e136761
title: Data and Code for: Disability Insurance in the Great Recession: Ease of Access, Program Enrollment, and Local Hysteresis

description: Previous research has documented that Social Security Disability Insurance (SSDI) applications and awards increase during economic downturns and that expanded access to SSDI leads to a reduction in employment. We build on these insights and investigate to what extent differential access to SSDI during economic downturns leads to differential changes in SSDI enrollment and employment during the subsequent recovery. We exploit plausibly exogenous variation in SSDI appeals processing time (a measure of hassle or access) facing individuals living in ZIP codes that straddle Social Security Administration hearing office catchment borders. During the Great Recession, ZIP codes assigned to hearing offices with faster appellate processes saw a larger increase in SSDI enrollment than their cross-border neighbors. These enrollment effects are concentrated among ZIP code pairs that experienced more severe labor market downturns, and they persist as late as 2015. In the full sample, there is no clear effect of longer processing times on subsequent employment rates. However, we find some limited evidence that faster appellate processes may have weighed on the employment recovery in hard-hit ZIP codes that had high pre-recession rates of SSDI enrollment. Our findings highlight the importance of considering interaction effects between economic shocks and ease of access to the safety net.<br>
description: We weight ZIP codes by their 2010 population. These weights are included in the analysis dataset.<br>
description: Adults aged 30–64 (for analysis of enrollment in Social Security Disability Insurance) or 30+ (for analysis of employment)<br>. Smallest Geographic Unit: ZIP code
DOI: 10.3886/e136761v1
title: Data and Code for: Disability Insurance in the Great Recession: Ease of Access, Program Enrollment, and Local Hysteresis

description: Previous research has documented that Social Security Disability Insurance (SSDI) applications and awards increase during economic downturns and that expanded access to SSDI leads to a reduction in employment. We build on these insights and investigate to what extent differential access to SSDI during economic downturns leads to differential changes in SSDI enrollment and employment during the subsequent recovery. We exploit plausibly exogenous variation in SSDI appeals processing time (a measure of hassle or access) facing individuals living in ZIP codes that straddle Social Security Administration hearing office catchment borders. During the Great Recession, ZIP codes assigned to hearing offices with faster appellate processes saw a larger increase in SSDI enrollment than their cross-border neighbors. These enrollment effects are concentrated among ZIP code pairs that experienced more severe labor market downturns, and they persist as late as 2015. In the full sample, there is no clear effect of longer processing times on subsequent employment rates. However, we find some limited evidence that faster appellate processes may have weighed on the employment recovery in hard-hit ZIP codes that had high pre-recession rates of SSDI enrollment. Our findings highlight the importance of considering interaction effects between economic shocks and ease of access to the safety net.<br>
description: We weight ZIP codes by their 2010 population. These weights are included in the analysis dataset.<br>
description: Adults aged 30–64 (for analysis of enrollment in Social Security Disability Insurance) or 30+ (for analysis of employment)<br>. Smallest Geographic Unit: ZIP code
DOI: 10.3886/e131723
title: Data and code for: Local Industrial Policy and Sectoral Hubs

description: We study the desirability of industrial policies that generate sectoral hubs using a quantitative spatial model with cognitive non-routine and other occupations. The productivity of each occupation in an industry depends on sector-specific production externalities, which we estimate using a model-implied instrumental variable approach. We find that the optimal policy gives rise to national hubs in coastal cities in tradeable services, like Professional Services, and smaller regional hubs in less tradable services, like Health and Education. The optimal policy prescribes developing Manufacturing in smaller towns. We decompose the implied changes in local costs and the available varieties in each sector.
description: Industry/City-level data on employment, wages and other auxiliary variables.
DOI: 10.3886/e131723v1
title: Data and code for: Local Industrial Policy and Sectoral Hubs

description: We study the desirability of industrial policies that generate sectoral hubs using a quantitative spatial model with cognitive non-routine and other occupations. The productivity of each occupation in an industry depends on sector-specific production externalities, which we estimate using a model-implied instrumental variable approach. We find that the optimal policy gives rise to national hubs in coastal cities in tradeable services, like Professional Services, and smaller regional hubs in less tradable services, like Health and Education. The optimal policy prescribes developing Manufacturing in smaller towns. We decompose the implied changes in local costs and the available varieties in each sector.
description: Industry/City-level data on employment, wages and other auxiliary variables.
DOI: 10.6084/m9.figshare.14502168
title: Dataset for Manuscript: An analysis of form and function of a research article between and within publishers and journals

description: Dataset resulting from an article heading form and function analysis across 12 publishers including both research articles and non research articles. Our aim was to: (1) Identify each of the labelled sections used by research articles, define these sections based on their rhetorical function, and determine frequency of use; (2) Within the given dataset, determine all of the alternative labels used to identify these sections; (3) Determine whether these sections can be used to consistently determine, a) whether an article is a true research article, or b) whether an article is <i>not</i> a research article. Results indicated wide variability in the organization of research articles with 24 common sections, known by 186 different names both within and across publishing houses.
DOI: 10.6084/m9.figshare.14502168.v1
title: Dataset for Manuscript: An analysis of form and function of a research article between and within publishers and journals

description: Dataset resulting from an article heading form and function analysis across 12 publishers including both research articles and non research articles. Our aim was to: (1) Identify each of the labelled sections used by research articles, define these sections based on their rhetorical function, and determine frequency of use; (2) Within the given dataset, determine all of the alternative labels used to identify these sections; (3) Determine whether these sections can be used to consistently determine, a) whether an article is a true research article, or b) whether an article is <i>not</i> a research article. Results indicated wide variability in the organization of research articles with 24 common sections, known by 186 different names both within and across publishing houses.
DOI: 10.3886/e131362
title: Replication Code for: Measuring Racial Discrimination in Algorithms

description: This Stata and R code replicates the analysis in Arnold, Dobbie, and Hull (2021). The data for this paper contains confidential information about criminal defendants in New York City and so is restricted-use. Accessing the data can be done by entering a data sharing agreement with the New York State Division of Criminal Justice Services and Office of Court Administration. Inquiries can be sent to:<br>DCJS Research Request TeamOffice of Justice Research and Performance, New York State Division of Criminal Justice Services 80 South Swan St., Albany, NY 12210DCJS.ResearchRequests@dcjs.ny.govwww.criminaljustice.ny.gov<br><br>An abstract of the project follows<br><br>There is growing concern that the rise of algorithmic decision-making can lead to discrimination against legally protected groups, but measuring such algorithmic discrimination is often hampered by a fundamental selection challenge. We develop new quasi-experimental tools to overcome this challenge and measure algorithmic discrimination in the setting of pretrial bail decisions. We first show that the selection challenge reduces to the challenge of measuring four moments: the mean latent qualification of white and Black individuals and the race-specific covariance between qualification and the algorithm’s treatment recommendation. We then show how these four moments can be estimated by extrapolating quasi-experimental variation across as-good-as-randomly assigned decision-makers. Estimates from New York City show that a sophisticated machine learning algorithm discriminates against Black defendants, even though defendant race and ethnicity are not included in the training data. The algorithm recommends releasing white defendants before trial at an 8 percentage point (11 percent) higher rate than Black defendants with identical potential for pretrial misconduct, with this unwarranted disparity explaining 77 percent of the observed racial disparity in algorithmic recommendations. We find a similar level of algorithmic discrimination with regression-based recommendations, using a model inspired by a widely used pretrial risk assessment tool.<br>
DOI: 10.3886/e131362v1
title: Replication Code for: Measuring Racial Discrimination in Algorithms

description: This Stata and R code replicates the analysis in Arnold, Dobbie, and Hull (2021). The data for this paper contains confidential information about criminal defendants in New York City and so is restricted-use. Accessing the data can be done by entering a data sharing agreement with the New York State Division of Criminal Justice Services and Office of Court Administration. Inquiries can be sent to:<br>DCJS Research Request TeamOffice of Justice Research and Performance, New York State Division of Criminal Justice Services 80 South Swan St., Albany, NY 12210DCJS.ResearchRequests@dcjs.ny.govwww.criminaljustice.ny.gov<br><br>An abstract of the project follows<br><br>There is growing concern that the rise of algorithmic decision-making can lead to discrimination against legally protected groups, but measuring such algorithmic discrimination is often hampered by a fundamental selection challenge. We develop new quasi-experimental tools to overcome this challenge and measure algorithmic discrimination in the setting of pretrial bail decisions. We first show that the selection challenge reduces to the challenge of measuring four moments: the mean latent qualification of white and Black individuals and the race-specific covariance between qualification and the algorithm’s treatment recommendation. We then show how these four moments can be estimated by extrapolating quasi-experimental variation across as-good-as-randomly assigned decision-makers. Estimates from New York City show that a sophisticated machine learning algorithm discriminates against Black defendants, even though defendant race and ethnicity are not included in the training data. The algorithm recommends releasing white defendants before trial at an 8 percentage point (11 percent) higher rate than Black defendants with identical potential for pretrial misconduct, with this unwarranted disparity explaining 77 percent of the observed racial disparity in algorithmic recommendations. We find a similar level of algorithmic discrimination with regression-based recommendations, using a model inspired by a widely used pretrial risk assessment tool.<br>
DOI: 10.25345/c5sr6h
title: MassIVE MSV000087328 - Sprotein Vaccine Skin Lesion Quantitative Proteome
title: Quantitative proteome analysis of skin lesions collected from mice infected subdermally with M1 Group A Streptococcus after immunization with recombinant S protein or injection with alum.
DOI: 10.6084/m9.figshare.14502177
title: Pristionchus pacificus csu60 Whole Genome Sequence

description: Whole genome sequencing data of <i>Pristionchus pacificus</i> dauer constitutive mutant allele, <i>csu60</i>.
DOI: 10.6084/m9.figshare.14498058
title: Supplementary Figure 7

description: Supplementary Figure 7 dataset<br>
DOI: 10.6084/m9.figshare.14498058.v1
title: Supplementary Figure 7

description: Supplementary Figure 7 dataset<br>
DOI: 10.6084/m9.figshare.14498055
title: Supplementary Figure 6

description: Supplementary Figure 6 dataset<br>
DOI: 10.6084/m9.figshare.14498055.v1
title: Supplementary Figure 6

description: Supplementary Figure 6 dataset<br>
DOI: 10.6084/m9.figshare.14498052
title: Supplementary Figure 5

description: Supplementary Figure 5 dataset<br>
DOI: 10.6084/m9.figshare.14498052.v1
title: Supplementary Figure 5

description: Supplementary Figure 5 dataset<br>
DOI: 10.6084/m9.figshare.14498049
title: Supplementary Figure 4

description: Supplementary Figure 4 dataset<br>
DOI: 10.6084/m9.figshare.14498049.v1
title: Supplementary Figure 4

description: Supplementary Figure 4 dataset<br>
DOI: 10.6084/m9.figshare.14498046
title: Supplementary Figure 3

description: Supplementary Figure 3 dataset<br>
DOI: 10.6084/m9.figshare.14498037
title: Supplementary Figure 1

description: Supplementary Figure 1 dataset
DOI: 10.6084/m9.figshare.14502174
title: IREDFisher_database.zip

description: structure database of IREDFisher
DOI: 10.6084/m9.figshare.14498037.v1
title: Supplementary Figure 1

description: Supplementary Figure 1 dataset
DOI: 10.6084/m9.figshare.14502174.v2
title: IREDFisher_database.zip

description: structure database of IREDFisher
DOI: 10.6084/m9.figshare.14502174.v1
title: IREDFisher_database.zip

description: structure database of IREDFisher
DOI: 10.6084/m9.figshare.14498034
title: Figure 4

description: Figure 4 dataset
DOI: 10.6084/m9.figshare.14498034.v1
title: Figure 4

description: Figure 4 dataset
DOI: 10.6084/m9.figshare.14498028
title: Figure 3

description: Figure 3 dataset
DOI: 10.6084/m9.figshare.14498028.v1
title: Figure 3

description: Figure 3 dataset
DOI: 10.6084/m9.figshare.14496093
title: Figure 1

description: Figure 1 dataset
DOI: 10.6084/m9.figshare.14496093.v1
title: Figure 1

description: Figure 1 dataset
DOI: 10.5281/zenodo.3965871
title: FakeCovid- A Multilingual Cross domain Fact Check Dataset for COVID-19

description: FakeCovid is the first multilingual cross-domain dataset of 7623 fact-checked news articles for COVID-19, collected from 04/01/2020 to 01/07/2020. We have collected the fact-checked articles from 92 fact-checking websites after obtaining references from Poynter and Snopes. We have manually annotated the collected articles into 11 categories of the fact-checked news according to their content. We ultimately generated dataset is in 40 languages from 105 countries.
description: {"references": ["Shahi, Gautam Kishore, and Durgesh Nandini. \"FakeCovid--A Multilingual Cross-domain Fact Check News Dataset for COVID-19.\" arXiv preprint arXiv:2006.11343 (2020)"]}
DOI: 10.5281/zenodo.3965870
title: FakeCovid- A Multilingual Cross domain Fact Check Dataset for COVID-19

description: FakeCovid is the first multilingual cross-domain dataset of 7623 fact-checked news articles for COVID-19, collected from 04/01/2020 to 01/07/2020. We have collected the fact-checked articles from 92 fact-checking websites after obtaining references from Poynter and Snopes. We have manually annotated the collected articles into 11 categories of the fact-checked news according to their content. We ultimately generated dataset is in 40 languages from 105 countries.
description: {"references": ["Shahi, Gautam Kishore, and Durgesh Nandini. \"FakeCovid--A Multilingual Cross-domain Fact Check News Dataset for COVID-19.\" arXiv preprint arXiv:2006.11343 (2020)"]}
DOI: 10.5517/ccdc.csd.cc25mby3
title: CCDC 2014595: Experimental Crystal Structure Determination

description: Related Article: Petr Švec, Maksim A. Samsonov, Zdeňka Růžičková, Jiří Brus, Aleš Růžička|2021|Dalton Trans.|50|5519|doi:10.1039/D1DT00704A
DOI: 10.5517/ccdc.csd.cc25mbz4
title: CCDC 2014596: Experimental Crystal Structure Determination

description: Related Article: Petr Švec, Maksim A. Samsonov, Zdeňka Růžičková, Jiří Brus, Aleš Růžička|2021|Dalton Trans.|50|5519|doi:10.1039/D1DT00704A
DOI: 10.5517/ccdc.csd.cc25mc06
title: CCDC 2014597: Experimental Crystal Structure Determination

description: Related Article: Petr Švec, Maksim A. Samsonov, Zdeňka Růžičková, Jiří Brus, Aleš Růžička|2021|Dalton Trans.|50|5519|doi:10.1039/D1DT00704A
DOI: 10.5517/ccdc.csd.cc25mc17
title: CCDC 2014598: Experimental Crystal Structure Determination

description: Related Article: Petr Švec, Maksim A. Samsonov, Zdeňka Růžičková, Jiří Brus, Aleš Růžička|2021|Dalton Trans.|50|5519|doi:10.1039/D1DT00704A
DOI: 10.5517/ccdc.csd.cc25mc28
title: CCDC 2014599: Experimental Crystal Structure Determination

description: Related Article: Petr Švec, Maksim A. Samsonov, Zdeňka Růžičková, Jiří Brus, Aleš Růžička|2021|Dalton Trans.|50|5519|doi:10.1039/D1DT00704A
DOI: 10.5517/ccdc.csd.cc26159r
title: CCDC 2026913: Experimental Crystal Structure Determination

description: Related Article: Lei Zhang, Fangfang Li, Jianjun You, Nengbin Hua, Qianting Wang, Junhui Si, Wenzhe Chen, Wenjing Wang, Xiaoyuan Wu, Wenbin Yang, Daqiang Yuan, Canzhong Lu, Yanrong Liu, Abdullah M. Al-Enizi, Ayman Nafady, Shengqian Ma|2021|Chemical Science|12|5767|doi:10.1039/D0SC06841A
DOI: 10.5517/ccdc.csd.cc2615bs
title: CCDC 2026914: Experimental Crystal Structure Determination

description: Related Article: Lei Zhang, Fangfang Li, Jianjun You, Nengbin Hua, Qianting Wang, Junhui Si, Wenzhe Chen, Wenjing Wang, Xiaoyuan Wu, Wenbin Yang, Daqiang Yuan, Canzhong Lu, Yanrong Liu, Abdullah M. Al-Enizi, Ayman Nafady, Shengqian Ma|2021|Chemical Science|12|5767|doi:10.1039/D0SC06841A
DOI: 10.5517/ccdc.csd.cc2615ct
title: CCDC 2026915: Experimental Crystal Structure Determination

description: Related Article: Lei Zhang, Fangfang Li, Jianjun You, Nengbin Hua, Qianting Wang, Junhui Si, Wenzhe Chen, Wenjing Wang, Xiaoyuan Wu, Wenbin Yang, Daqiang Yuan, Canzhong Lu, Yanrong Liu, Abdullah M. Al-Enizi, Ayman Nafady, Shengqian Ma|2021|Chemical Science|12|5767|doi:10.1039/D0SC06841A
DOI: 10.5517/ccdc.csd.cc26bh02
title: CCDC 2035863: Experimental Crystal Structure Determination

description: Related Article: Shitao Wang, Chaoxian Yan, Wenlong Zhao, Xiaolan Liu, Cheng-Shan Yuan, Hao-Li Zhang, Xiangfeng Shao|2021|Chemical Science|12|5811|doi:10.1039/D1SC00397F
DOI: 10.5517/ccdc.csd.cc26bh24
title: CCDC 2035865: Experimental Crystal Structure Determination

description: Related Article: Shitao Wang, Chaoxian Yan, Wenlong Zhao, Xiaolan Liu, Cheng-Shan Yuan, Hao-Li Zhang, Xiangfeng Shao|2021|Chemical Science|12|5811|doi:10.1039/D1SC00397F
DOI: 10.5517/ccdc.csd.cc26bh35
title: CCDC 2035866: Experimental Crystal Structure Determination

description: Related Article: Shitao Wang, Chaoxian Yan, Wenlong Zhao, Xiaolan Liu, Cheng-Shan Yuan, Hao-Li Zhang, Xiangfeng Shao|2021|Chemical Science|12|5811|doi:10.1039/D1SC00397F
DOI: 10.5517/ccdc.csd.cc26bh57
title: CCDC 2035868: Experimental Crystal Structure Determination

description: Related Article: Shitao Wang, Chaoxian Yan, Wenlong Zhao, Xiaolan Liu, Cheng-Shan Yuan, Hao-Li Zhang, Xiangfeng Shao|2021|Chemical Science|12|5811|doi:10.1039/D1SC00397F