cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9955133
title: MCSP_Nigeria LDHF_Study_OSCE Scores_CODEBOOK.csv

description: The aim of this study was to compare the knowledge and skills competencies of providers who attended training in LDHF/m-mentoring with TRAD approaches in improving maternal and newborn care on the day of birth in Ebonyi and Kogi states, Nigeria. The study’s primary outcomes were increase in knowledge, clinical skills in BEmONC, and retention of clinical competency at 3- and 12-months post-training. The secondary outcomes measured were facilitators of and barriers to the LDHF/m-mentoring training approach at individual and institutional levels
DOI: 10.6084/m9.figshare.9955133.v1
title: MCSP_Nigeria LDHF_Study_OSCE Scores_CODEBOOK.csv

description: The aim of this study was to compare the knowledge and skills competencies of providers who attended training in LDHF/m-mentoring with TRAD approaches in improving maternal and newborn care on the day of birth in Ebonyi and Kogi states, Nigeria. The study’s primary outcomes were increase in knowledge, clinical skills in BEmONC, and retention of clinical competency at 3- and 12-months post-training. The secondary outcomes measured were facilitators of and barriers to the LDHF/m-mentoring training approach at individual and institutional levels
DOI: 10.5281/zenodo.4001601
title: Python Annotated Code Search (PACS) Datasets & Pretrained Models

description: This upload contains datasets and pre-trained models used for the paper <em>Neural Code Search Revisited: Enhancing Code Snippet Retrieval through Natural Language Intent. </em>The code for easily loading these datasets and models will be made available here: http://github.com/nokia/codesearch <strong>Datasets</strong><br> There are three types of datasets: snippet collections (code snippets + natural language descriptions): so-ds-feb20, staqc-py-cleaned, conala-curated code search evaluation data (queries linked to relevant snippets of one of the snippet collections): so-ds-feb20-{valid|test}, staqc-py-raw-{valid|test}, conala-curated-0.5-test training data (datasets used to train code retrieval models): so-duplicates-pacs-train, so-python-question-titles-feb20 The staqc-py-cleaned snippet collection, and the conala-curated datasets were derived from existing corpora: staqc-py-cleaned was derived from the Python StaQC snippet collection. See https://github.com/LittleYUYU/StackOverflow-Question-Code-Dataset, LICENSE. conala-curated was derived from the conala corpus. See https://conala-corpus.github.io/ , LICENSE The other datasets were mined directly from a recent Stack Overflow dump (https://archive.org/details/stackexchange, LICENSE). <br> <br> <strong>Pre-trained models</strong><br> Each model can embed queries and (annotated) code snippets in the same space. The models are released under a BSD 3-Clause License. ncs-embedder-so-ds-feb20 ncs-embedder-staqc-py tnbow-embedder-so-ds-feb20 use-embedder-pacs ensemble-embedder-pacs
DOI: 10.6084/m9.figshare.9954992
title: PTA gender supplemental

description: qRT-PCR Primer for Genes information and Antibodies Used in This Study.
DOI: 10.6084/m9.figshare.9955058
title: grid.1001.0

description: What does Australasian Research Look Like Data for institution
DOI: 10.6084/m9.figshare.9954992.v1
title: PTA gender supplemental

description: qRT-PCR Primer for Genes information and Antibodies Used in This Study.
DOI: 10.6084/m9.figshare.9954989.v1
title: Heteroscedastic BART Via Multiplicative Regression Trees

description: BART (Bayesian Additive Regression Trees) has become increasingly popular as a flexible and scalable nonparametric regression approach for modern applied statistics problems. For the practitioner dealing with large and complex nonlinear response surfaces, its advantages include a matrix-free formulation and the lack of a requirement to prespecify a confining regression basis. Although flexible in fitting the mean, BART has been limited by its reliance on a constant variance error model. Alleviating this limitation, we propose HBART, a nonparametric heteroscedastic elaboration of BART. In BART, the mean function is modeled with a sum of trees, each of which determines an additive contribution to the mean. In HBART, the variance function is further modeled with a product of trees, each of which determines a multiplicative contribution to the variance. Like the mean model, this flexible, multidimensional variance model is entirely nonparametric with no need for the prespecification of a confining basis. Moreover, with this enhancement, HBART can provide insights into the potential relationships of the predictors with both the mean and the variance. Practical implementations of HBART with revealing new diagnostic plots are demonstrated with simulated and real data on used car prices and song year of release. Supplemental materials are available online.
DOI: 10.5281/zenodo.3997362
title: Equilibrium geometry configurations of DMMI and DMHI chromophores in gas phase and microsolvation models

description: Gas phase and microsolvation models are marked as "gas" and "solv" in the file names. Cis- and trans-enol formes are marked as "CIS" and "TRANS", respectively; keto form has "KETO" in the file name.
DOI: 10.5281/zenodo.3997361
title: Equilibrium geometry configurations of DMMI and DMHI chromophores in gas phase and microsolvation models

description: Gas phase and microsolvation models are marked as "gas" and "solv" in the file names. Cis- and trans-enol formes are marked as "CIS" and "TRANS", respectively; keto form has "KETO" in the file name.
DOI: 10.6084/m9.figshare.9952469
title: Metadata record for: A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor

description: This dataset contains key characteristics about the data described in the Data Descriptor A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format<br><br>Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.<br>
DOI: 10.6084/m9.figshare.9952469.v2
title: Metadata record for: A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor

description: This dataset contains key characteristics about the data described in the Data Descriptor A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format<br><br>Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.<br>
DOI: 10.6084/m9.figshare.9952469.v1
title: Metadata record for: A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor

description: This dataset contains key characteristics about the data described in the Data Descriptor A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.6084/m9.figshare.9949139
title: The Effects of Short-Term Rental Regulation in San Francisco

description: Data used for The Effects of Short-Term Rental Regulation in San Francisco. Data sources are available on the paper.sf = time series;27zipcodes = panel.
DOI: 10.6084/m9.figshare.9949181
title: Supplementary Material for: The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis

description: <b><i>Background:</i></b> Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results. <b><i>Objective:</i></b> To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10. <b><i>Methods:</i></b> Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview. <b><i>Results:</i></b> Data were included for 54 of 72 identified eligible studies (<i>n</i> participants = 16,688, <i>n</i> cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22–0.24 lower compared to fully structured interviews and 0.06–0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82–0.92) and 0.86 (0.82–0.88). <b><i>Conclusions:</i></b> The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.
DOI: 10.6084/m9.figshare.9949139.v1
title: The Effects of Short-Term Rental Regulation in San Francisco

description: Data used for The Effects of Short-Term Rental Regulation in San Francisco. Data sources are available on the paper.sf = time series;27zipcodes = panel.
DOI: 10.6084/m9.figshare.9949055
title: Supplementary Material for: Pattern Recognition to Identify Stroke in the Cognitive Profile: Secondary Analyses of a Prospective Cohort Study

description: <b><i>Background:</i></b> Stroke can produce subtle changes in the brain that may produce symptoms that are too small to lead to a diagnosis. Noting that a lack of diagnosis may bias research estimates, the current study sought to examine the utility of pattern recognition relying on serial assessments of cognition to objectively identify stroke-like patterns of cognitive decline (pattern-detected stroke, p-stroke). <b><i>Methods:</i></b> Secondary data analysis was conducted using participants with no reported history of stroke in the <i>Health and Retirement Study</i>, a large (<i>n</i> = 16,113) epidemiological study of cognitive aging among respondents aged 50 years and older that measured episodic memory consistently biennially between 1996 and 2014. Analyses were limited to participants with at least 4 serial measures of episodic memory. Occurrence and date of p-stroke events were identified utilizing pattern recognition to identify stepwise declines in cognition consistent with stroke. Descriptive statistics included the percentage of the population with p-stroke, the mean change in episodic memory resulting in stroke-positive testing, and the mean time between p-stroke and first major diagnosed stroke. Statistical analyses comparing cases of p-stroke with reported major stroke relied on the area under the receiver-operating curve (AUC). Longitudinal modeling was utilized to examine rates of change in those with/without major stroke after adjusting for demographics. <b><i>Results:</i></b> The pattern recognition protocol identified 7,499 p-strokes that went unreported. On average, individuals with p-stroke declined in episodic memory by 1.986 (SD = 0.023) words at the inferred time of stroke. The resulting pattern recognition protocol was able to identify self-­reported major stroke (AUC = 0.58, 95% CI = 0.57–0.59, <i>p</i> &lt; 0.001). In those with a reported major stroke, p-stroke events were detectable on average 4.963 (4.650–5.275) years (<i>p</i> &lt; 0.001) before diagnosis was first reported. The incidence of p-stroke was 40.23/1,000 (95% CI = 39.40–41.08) person-years. After adjusting for sex, age was associated with the incidence of p-stroke and major stroke at similar rates. <b><i>Conclusions:</i></b> This is the first study to propose utilizing pattern recognition to identify the incidence and timing of p-stroke. Further work is warranted examining the clinical utility of pattern recognition in identifying p-stroke in longitudinal cognitive profiles.
DOI: 10.6084/m9.figshare.9949046
title: Supplemental Data.docx

description: Comparison of aldosterone LC-MS/MS Assay vs. Immunoassay (n=212).
DOI: 10.6084/m9.figshare.9949055.v1
title: Supplementary Material for: Pattern Recognition to Identify Stroke in the Cognitive Profile: Secondary Analyses of a Prospective Cohort Study

description: <b><i>Background:</i></b> Stroke can produce subtle changes in the brain that may produce symptoms that are too small to lead to a diagnosis. Noting that a lack of diagnosis may bias research estimates, the current study sought to examine the utility of pattern recognition relying on serial assessments of cognition to objectively identify stroke-like patterns of cognitive decline (pattern-detected stroke, p-stroke). <b><i>Methods:</i></b> Secondary data analysis was conducted using participants with no reported history of stroke in the <i>Health and Retirement Study</i>, a large (<i>n</i> = 16,113) epidemiological study of cognitive aging among respondents aged 50 years and older that measured episodic memory consistently biennially between 1996 and 2014. Analyses were limited to participants with at least 4 serial measures of episodic memory. Occurrence and date of p-stroke events were identified utilizing pattern recognition to identify stepwise declines in cognition consistent with stroke. Descriptive statistics included the percentage of the population with p-stroke, the mean change in episodic memory resulting in stroke-positive testing, and the mean time between p-stroke and first major diagnosed stroke. Statistical analyses comparing cases of p-stroke with reported major stroke relied on the area under the receiver-operating curve (AUC). Longitudinal modeling was utilized to examine rates of change in those with/without major stroke after adjusting for demographics. <b><i>Results:</i></b> The pattern recognition protocol identified 7,499 p-strokes that went unreported. On average, individuals with p-stroke declined in episodic memory by 1.986 (SD = 0.023) words at the inferred time of stroke. The resulting pattern recognition protocol was able to identify self-­reported major stroke (AUC = 0.58, 95% CI = 0.57–0.59, <i>p</i> &lt; 0.001). In those with a reported major stroke, p-stroke events were detectable on average 4.963 (4.650–5.275) years (<i>p</i> &lt; 0.001) before diagnosis was first reported. The incidence of p-stroke was 40.23/1,000 (95% CI = 39.40–41.08) person-years. After adjusting for sex, age was associated with the incidence of p-stroke and major stroke at similar rates. <b><i>Conclusions:</i></b> This is the first study to propose utilizing pattern recognition to identify the incidence and timing of p-stroke. Further work is warranted examining the clinical utility of pattern recognition in identifying p-stroke in longitudinal cognitive profiles.
DOI: 10.6084/m9.figshare.9949046.v1
title: Supplemental Data.docx

description: Comparison of aldosterone LC-MS/MS Assay vs. Immunoassay (n=212).
DOI: 10.6084/m9.figshare.9949010
title: grid.1012.2

description: What does Australasian Research Look Like Data for institution
DOI: 10.6084/m9.figshare.9949010.v1
title: grid.1012.2

description: What does Australasian Research Look Like Data for institution
DOI: 10.6084/m9.figshare.9948878
title: Supplementary Material for: The Associations between Antenatal Corticosteroids and In-Hospital Outcomes of Preterm Singleton Appropriate for Gestational Age Neonates according to the Presence of Maternal Histologic Chorioamnionitis

description: <b><i>Introduction:</i></b> This study aimed to assess the association between antenatal corticosteroid (ACS) and in-hospital outcomes of preterm singleton appropriate for gestational age (AGA) infants according to the presence of maternal histologic chorioamnionitis (HCA). <b><i>Methods:</i></b> A retrospective study was performed with singleton AGA neonates of 23<sup>+0</sup> to 33<sup>+6</sup> weeks’ gestation born between 2007 and 2014. We compared the clinical outcomes according to the presence of HCA and ACS use. We also divided the ACS group into 2 groups: infants who received ACS 2–7 days before birth (optimal ACS) or not (suboptimal ACS). Multivariate logistic regression with Firth’s penalized likelihood was performed. <b><i>Results:</i></b> In total, 254 neonates were eligible with 109 neonates with HCA (42.9%). In multivariate analysis adjusting for GA, sex, and cesarean section, ACS use was associated with reduced severe bronchopulmonary dysplasia (BPD) or death and hypotension within 7 postnatal days among the neonates with HCA. However, it was associated with increased patent ductus arteriosus (PDA) treatment. In the optimal ACS group, severe BPD or death (aOR 0.03, 95% CI 0.01–0.42), hypotension (aOR 0.02, 95% CI 0.01–0.26), and inhaled nitric oxide use (aOR 0.06, 95% CI 0.00–0.81) were lower, however, PDA treatment (aOR 8.14, 95% CI 1.20–55.24) and sepsis (aOR 6.85, 95% CI 1.02–46.07) were higher when compared with the no ACS group among HCA+ infants. Among HCA– infants, only PDA treatment was lower in the ACS group. <b><i>Conclusion:</i></b> In neonates with HCA, ACS treatment was associated with reduced morbidities. However, increased sepsis was associated with optimal ACS use.
DOI: 10.6084/m9.figshare.9948902.v1
title: Test

description: test dataset
DOI: 10.6084/m9.figshare.9948803
title: Metadata record for: Classification of GABAergic interneurons by leading neuroscientists

description: This dataset contains key characteristics about the data described in the Data Descriptor Classification of GABAergic interneurons by leading neuroscientists. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format<br><br>Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.
DOI: 10.6084/m9.figshare.9948785
title: Supplementary Material for: Objective Response by mRECIST Is an Independent Prognostic Factor for Overall Survival in Hepatocellular Carcinoma Treated with Sorafenib in the SILIUS Trial

description: <b><i>Objective:</i></b> In SILIUS (NCT01214343), combination of sorafenib and hepatic arterial infusion chemotherapy did not significantly improve overall survival (OS) in patients with advanced hepatocellular carcinoma (HCC) compared with sorafenib alone. In this study, we explored the relationship between objective response by mRECIST and OS in the sorafenib group, in the combination group, and in all patients in the SILIUS trial. <b><i>Methods:</i></b> Association between objective response and OS in patients treated with sorafenib (<i>n</i> = 103) or combination (<i>n</i> = 102) and all patients (<i>n</i> = 205) were analyzed. The median OS of responders was compared with that of non-responders. Landmark analyses were performed according to objective response at several fixed time points, as sensitivity analyses, and the effect on OS was evaluated by Cox regression analysis with objective response as a time-dependent covariate, with other prognostic factors. <b><i>Results:</i></b> In the sorafenib group, OS of responders (<i>n</i> = 18) was significantly better than that of non-responders (<i>n</i> = 78) (<i>p</i> &lt; 0.0001), where median OS was 27.2 (95% CI, 16.0–not reached) months for responders and 8.9 (95% CI, 6.5–12.6) months for non-responders. HRs from landmark analyses at 4, 6, and 8 months were 0.45 (<i>p</i> = 0.0330), 0.37 (<i>p</i> = 0.0053), and 0.36 (<i>p</i> = 0.0083), respectively. Objective response was an independent predictor of OS based on unstratified Cox regression analyses. In the all patients and the combination group, similar results were obtained. <b><i>Conclusions:</i></b> In the SILIUS trial, objective response by sorafenib assessed by mRECIST is an independent prognostic factor for OS in patients with HCC.
DOI: 10.6084/m9.figshare.9948803.v2
title: Metadata record for: Classification of GABAergic interneurons by leading neuroscientists

description: This dataset contains key characteristics about the data described in the Data Descriptor Classification of GABAergic interneurons by leading neuroscientists. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format<br><br>Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.
DOI: 10.6084/m9.figshare.9948785.v1
title: Supplementary Material for: Objective Response by mRECIST Is an Independent Prognostic Factor for Overall Survival in Hepatocellular Carcinoma Treated with Sorafenib in the SILIUS Trial

description: <b><i>Objective:</i></b> In SILIUS (NCT01214343), combination of sorafenib and hepatic arterial infusion chemotherapy did not significantly improve overall survival (OS) in patients with advanced hepatocellular carcinoma (HCC) compared with sorafenib alone. In this study, we explored the relationship between objective response by mRECIST and OS in the sorafenib group, in the combination group, and in all patients in the SILIUS trial. <b><i>Methods:</i></b> Association between objective response and OS in patients treated with sorafenib (<i>n</i> = 103) or combination (<i>n</i> = 102) and all patients (<i>n</i> = 205) were analyzed. The median OS of responders was compared with that of non-responders. Landmark analyses were performed according to objective response at several fixed time points, as sensitivity analyses, and the effect on OS was evaluated by Cox regression analysis with objective response as a time-dependent covariate, with other prognostic factors. <b><i>Results:</i></b> In the sorafenib group, OS of responders (<i>n</i> = 18) was significantly better than that of non-responders (<i>n</i> = 78) (<i>p</i> &lt; 0.0001), where median OS was 27.2 (95% CI, 16.0–not reached) months for responders and 8.9 (95% CI, 6.5–12.6) months for non-responders. HRs from landmark analyses at 4, 6, and 8 months were 0.45 (<i>p</i> = 0.0330), 0.37 (<i>p</i> = 0.0053), and 0.36 (<i>p</i> = 0.0083), respectively. Objective response was an independent predictor of OS based on unstratified Cox regression analyses. In the all patients and the combination group, similar results were obtained. <b><i>Conclusions:</i></b> In the SILIUS trial, objective response by sorafenib assessed by mRECIST is an independent prognostic factor for OS in patients with HCC.
DOI: 10.6084/m9.figshare.9948803.v1
title: Metadata record for: Classification of GABAergic interneurons by leading neuroscientists

description: This dataset contains key characteristics about the data described in the Data Descriptor Classification of GABAergic interneurons by leading neuroscientists. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format