cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.8248073.v1
title: Bridge Centrality: A Network Approach to Understanding Comorbidity

description: Recently, researchers in clinical psychology have endeavored to create network models of the relationships between symptoms, both within and across mental disorders. Symptoms that connect two mental disorders are called "bridge symptoms." Unfortunately, no formal quantitative methods for identifying these bridge symptoms exist. Accordingly, we developed four network statistics to identify bridge symptoms: <i>bridge strength</i>, <i>bridge betweenness, bridge closeness</i>, and <i>bridge expected influence</i>. These statistics are nonspecific to the type of network estimated, making them potentially useful in individual-level psychometric networks, group-level psychometric networks, and networks outside the field of psychopathology such as social networks. We first tested the fidelity of our statistics in predicting bridge nodes in a series of simulations. Averaged across all conditions, the statistics achieved a sensitivity of 92.7% and a specificity of 84.9%. By simulating datasets of varying sample sizes, we tested the robustness of our statistics, confirming their suitability for network psychometrics. Furthermore, we simulated the contagion of one mental disorder to another, showing that deactivating bridge nodes prevents the spread of comorbidity (i.e., one disorder activating another). Eliminating nodes based on bridge statistics was more effective than eliminating nodes high on traditional centrality statistics in preventing comorbidity. Finally, we applied our algorithms to 18 group-level empirical comorbidity networks from published studies and discussed the implications of this analysis.
DOI: 10.6084/m9.figshare.12849689
title: Sampling Variability Is Not Nonreplication: A Bayesian Reanalysis of Forbes, Wright, Markon, and Krueger

description: Forbes, Wright, Markon, and Krueger claim that psychopathology network characteristics have “limited” or “poor” replicability, supporting their argument primarily with data from two waves of an observational study on depression and anxiety. They developed “direct metrics” to gauge change across networks (e.g., change in edge sign), and used these results to support their conclusion. Three key flaws undermine their critique. First, nonreplication across empirical datasets does not provide evidence against a method; such evaluations of methods are possible only in controlled simulations when the data-generating model is known. Second, they assert that the removal of shared variance necessarily decreases reliability. This is not true. Depending on the causal model, it can either increase or decrease reliability. Third, their direct metrics do not account for normal sampling variability, leaving open the possibility that the direct differences between samples are due to normal, unproblematic fluctuations. As an alternative to their direct metrics, we provide a Bayesian re-analysis that quantifies uncertainty and compares relative evidence for replication (i.e., equivalence) versus nonreplication (i.e., nonequivalence) for each network edge. This approach provides a principled roadmap for future assessments of network replicability. Our analysis indicated substantial evidence for replication and scant evidence for nonreplication.
DOI: 10.6084/m9.figshare.23301469
title: Investigating the Utility of Fixed-margin Sampling in Network Psychometrics

description: Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. We argue that fixed-margin sampling cannot be used for this purpose, as it generates data under a particular null-hypothesis: a unidimensional factor model with interchangeable indicators (i.e., the Rasch model). We show this by discussing relevant psychometric literature and by performing simulation studies. Results indicate that while eLasso correctly estimated network models and estimated almost no edges due to chance, fixed-margin sampling performed poorly in classifying true effects as “interesting” (Steinley et al. 2017, p. 1004). Further simulation studies indicate that fixed-margin sampling offers a powerful method for highlighting local misfit from the Rasch model, but performs only moderately in identifying global departures from the Rasch model. We conclude that fixed-margin sampling is not up to the task of assessing if results from estimated Ising models or other multivariate psychometric models are due to chance.
DOI: 10.6084/m9.figshare.23301469.v1
title: Investigating the Utility of Fixed-margin Sampling in Network Psychometrics

description: Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. We argue that fixed-margin sampling cannot be used for this purpose, as it generates data under a particular null-hypothesis: a unidimensional factor model with interchangeable indicators (i.e., the Rasch model). We show this by discussing relevant psychometric literature and by performing simulation studies. Results indicate that while eLasso correctly estimated network models and estimated almost no edges due to chance, fixed-margin sampling performed poorly in classifying true effects as “interesting” (Steinley et al. 2017, p. 1004). Further simulation studies indicate that fixed-margin sampling offers a powerful method for highlighting local misfit from the Rasch model, but performs only moderately in identifying global departures from the Rasch model. We conclude that fixed-margin sampling is not up to the task of assessing if results from estimated Ising models or other multivariate psychometric models are due to chance.
DOI: 10.6084/m9.figshare.12849689.v1
title: Sampling Variability Is Not Nonreplication: A Bayesian Reanalysis of Forbes, Wright, Markon, and Krueger

description: Forbes, Wright, Markon, and Krueger claim that psychopathology network characteristics have “limited” or “poor” replicability, supporting their argument primarily with data from two waves of an observational study on depression and anxiety. They developed “direct metrics” to gauge change across networks (e.g., change in edge sign), and used these results to support their conclusion. Three key flaws undermine their critique. First, nonreplication across empirical datasets does not provide evidence against a method; such evaluations of methods are possible only in controlled simulations when the data-generating model is known. Second, they assert that the removal of shared variance necessarily decreases reliability. This is not true. Depending on the causal model, it can either increase or decrease reliability. Third, their direct metrics do not account for normal sampling variability, leaving open the possibility that the direct differences between samples are due to normal, unproblematic fluctuations. As an alternative to their direct metrics, we provide a Bayesian re-analysis that quantifies uncertainty and compares relative evidence for replication (i.e., equivalence) versus nonreplication (i.e., nonequivalence) for each network edge. This approach provides a principled roadmap for future assessments of network replicability. Our analysis indicated substantial evidence for replication and scant evidence for nonreplication.
DOI: 10.15468/dl.36ptkg
title: Occurrence Download

description: A dataset containing 178309 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Machine Observation",
 "TaxonKey is Vulpes vulpes (Linnaeus, 1758)"
 ]
}

 The dataset includes 178309 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021859-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.14526639
title: Effects of Spatial Density of Public Places to the Intensity of COVID-19 Positive Cases Raw Data

description: Effects of Spatial Density of Public Places to the Intensity of COVID-19 Positive Cases Raw Data for F1000 Publication
DOI: 10.6084/m9.figshare.14526639.v1
title: Effects of Spatial Density of Public Places to the Intensity of COVID-19 Positive Cases Raw Data

description: Effects of Spatial Density of Public Places to the Intensity of COVID-19 Positive Cases Raw Data for F1000 Publication
DOI: 10.34740/kaggle/dsv/2183179
title: Herbarium 2021 RBS
DOI: 10.6084/m9.figshare.14515863
title: Knowledge of community pharmacists in the Kathmandu Valley, Nepal about the risks associated with medication use during pregnancy

description: The dataset describes the knowledge of community pharmacists in the Kathmandu valley, Nepal about the use of different medications during pregnancy. The most dispensed groups of medicines by the CPs, their major concern while dispensing medicines to the pregnant women and the most used resources to obtain information while dispensing medicines were also studied. The demographic characteristics of the community pharmacists is also provided.
DOI: 10.5281/zenodo.4732822
title: Database_Aedes_Culex_LTC_captures

description: Excel database featuring Aedes and Culex mosquito captures from CDC Light Traps. Data collected throughout the rainy seasons 2013 and 2104 in the Kossi Region, Burkina Faso for the EMIRA Project.
description: File contains the main datasheet and another sheet explaining the variables
DOI: 10.5281/zenodo.4732821
title: Database_Aedes_Culex_LTC_captures

description: Excel database featuring Aedes and Culex mosquito captures from CDC Light Traps. Data collected throughout the rainy seasons 2013 and 2104 in the Kossi Region, Burkina Faso for the EMIRA Project.
description: File contains the main datasheet and another sheet explaining the variables
DOI: 10.15161/oar.it/73757
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.4718325
title: In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations: figure data & analysis code

description: Tabular data and analysis code corresponding to figures 2 through 5 (and supplementary figures 1 through 6) in the 2021 Nature Communcations publication entitled "In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations". Tabular data are provided for each figure in the form of excel spreadsheets, with individual data sheets for each figure sub-panel, where all axis and units are described in the row and column headings. Additionally, the ipython notebooks used to generate the figure data are provided (figure*.ipynb), together with the necessary raw data files (data.zip), supporting libraries (utils.zip), output folder (figures.zip), and requirements (requirements.txt). See README.rtf for detailed information and usage instructions.
DOI: 10.25646/8435
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.6084/m9.figshare.14526873
title: 2018.xlsx

description: BEHAVIOUR IL
DOI: 10.6084/m9.figshare.14526873.v1
title: 2018.xlsx

description: BEHAVIOUR IL
DOI: 10.6084/m9.figshare.14526885
title: 2018.xlsx

description: Process
DOI: 10.6084/m9.figshare.14526885.v2
title: 2018.xlsx

description: Process
DOI: 10.6084/m9.figshare.14526885.v1
title: 2018.xlsx

description: Process
DOI: 10.25919/6whj-7355
title: Parkes observations for project P1068 semester 2021APRS_01

description: In the fast-moving world of Fast Radio Bursts (FRBs), the critical question of what fraction of FRBs emit repeat bursts remains unanswered. Of order 20 repeating FRBs are now known, and their spectro-temporal properties hint at differences with apparently non-repeating bursts - the poor statistics preclude a definitive diagnosis. FRB 180301 is a promising source for further study for multiple reasons: it is an active repeater similar to the FRB 121102 and the most active FRB source visible to Parkes, and it shows diverse polarization properties across the repeat bursts. We have detected multiple repeat bursts from this source in our campaign last semester. The signal-to-noise ratio (S/N) of these detections are not sufficiently significant to measure their spectro-polarimetric properties. We request Parkes observations with the UWL receiver to continue the monitoring of this FRB source in order to characterize the broadband emission properties. Some of the key goals for these future observations are: to constrain the repetition rate, identify any variation of pulse characteristics over time, measure the polarimetric properties and provide insight into the emission mechanisms. The diverse polarization angle swings in the FAST detections and significant circular polarization in the original Parkes detection indicate the progenitor is embedded in an extreme magneto-ionic environment with complex field structure that has not been seen before. Understanding these diverse polarization properties from this source could be the key to distinguish repeater sources from the apparent non-repeaters ones.
DOI: 10.5281/zenodo.4732896
title: Supplementary Material for "Challenges of Mining Solution Snippets from Stack Overflow: A Taxonomy to Guide Reusability"

description: Stack Overflow is the de facto standard for finding answers to programming problems, many of which include code snippets in the solutions. Unfortunately, it is not always easy for developers to identify a reusable code snippet that solves a specific programming problem as the answers provided on Stack Overflow often contain fixes and source code that only apply in a specific context, and can include a variety of other content, such as examples of how to use the code. Some answers even include incorrect ways to solve a problem. In this paper, we explore the reusability of what we call Solution Snippets to help developers find solutions to their problems. As part of this work, we conducted an empirical study to first understand the characteristics of questions that would typically be answered with a Solution Snippet, and then to understand the characteristics of Solution Snippets themselves and how they may be reused by developers. Through an exploratory study of 598 Stack Overflow answers, we: (1) identify the characteristics of questions that need to be addressed with a Solution Snippet (how-to questions); (2) identify how Solution Snippets are presented in the answers to those questions; (3) classify Solution Snippets according to their reusability; and (4) provide suggestions for Stack Overflow designers to improve the presentation of answers on Stack Overflow in a way that facilitates reusability and automatic extraction of the information.
DOI: 10.5281/zenodo.4723989
title: Supplementary Material for "Challenges of Mining Solution Snippets from Stack Overflow: A Taxonomy to Guide Reusability"

description: Stack Overflow is the de facto standard for finding answers to programming problems, many of which include code snippets in the solutions. Unfortunately, it is not always easy for developers to identify a reusable code snippet that solves a specific programming problem as the answers provided on Stack Overflow often contain fixes and source code that only apply in a specific context, and can include a variety of other content, such as examples of how to use the code. Some answers even include incorrect ways to solve a problem. In this paper, we explore the reusability of what we call Solution Snippets to help developers find solutions to their problems. As part of this work, we conducted an empirical study to first understand the characteristics of questions that would typically be answered with a Solution Snippet, and then to understand the characteristics of Solution Snippets themselves and how they may be reused by developers. Through an exploratory study of 598 Stack Overflow answers, we: (1) identify the characteristics of questions that need to be addressed with a Solution Snippet (how-to questions); (2) identify how Solution Snippets are presented in the answers to those questions; (3) classify Solution Snippets according to their reusability; and (4) provide suggestions for Stack Overflow designers to improve the presentation of answers on Stack Overflow in a way that facilitates reusability and automatic extraction of the information.
DOI: 10.7910/dvn/kkqfnx
title: Transfer to AQoL-6D Utility Algorithms (Outputs of Secondary Analysis B)

description: Content in this dataset is currently private, pending publication of a supporting scientific manuscript. When published this dataset will make available a collection of models that can be used to predict AQoL-6D health utility in young people. The models in this dataset are supplementary to those produced in the main analysis. This dataset is provided so that others can apply the algorithms we have developed, consistent with the principles of the ready4 open science framework for data synthesis and simulation in mental health.
DOI: 10.5517/ccdc.csd.cc261p32
title: CCDC 2027403: Experimental Crystal Structure Determination

description: Related Article: Cong-Cong Chen, Yue Cai, Long-Fei Wang, Yun-Dang Wu, Hao-Jun Yin, Jia-Rong Zhou, Chun-Lin Ni, Wei Liu|2021|Inorg.Chem.|60|5463|doi:10.1021/acs.inorgchem.0c02853
DOI: 10.6084/m9.figshare.14526876
title: Supplementary data to the paper: Omega-3 polyunsaturated fatty acid biomarkers and risk of type 2 diabetes, cardiovascular disease, cancer, and mortality: A dose-response meta-analysis of prospective studies

description: Supplementary data belonging to omega-3 polyunsaturated fatty acid biomarkers and risk of type 2 diabetes, cardiovascular disease, cancer, and mortality: A dose-response meta-analysis of prospective studies<br>
DOI: 10.6084/m9.figshare.14526876.v1
title: Supplementary data to the paper: Omega-3 polyunsaturated fatty acid biomarkers and risk of type 2 diabetes, cardiovascular disease, cancer, and mortality: A dose-response meta-analysis of prospective studies

description: Supplementary data belonging to omega-3 polyunsaturated fatty acid biomarkers and risk of type 2 diabetes, cardiovascular disease, cancer, and mortality: A dose-response meta-analysis of prospective studies<br>
DOI: 10.5281/zenodo.4732633
title: Raytrace Simulation Results: WWV → WA5FRF, 2.5, 5, 10 MHz, IRI, 1 October 2019

description: IRI simulation from WWV to WA5FRF on the day of the WWV Centennial Festival of Frequency Measurement. Visualization here: https://youtu.be/D23DhteWOV0
description: {"references": ["10.1109/LGRS.2021.3063361"]}
DOI: 10.5281/zenodo.4722265
title: Raytrace Simulation Results: WWV → WA9VNJ, SAMI3, 10 MHz, 17 August 2017, Base and Eclipse

description: SAMI3 simulation, with and without the eclipse included in the simulation. You can see the video here: https://www.youtube.com/watch?v=a5QuitNRvcM
DOI: 10.5281/zenodo.4732632
title: Raytrace Simulation Results: WWV → WA5FRF, 2.5, 5, 10 MHz, IRI, 1 October 2019

description: IRI simulation from WWV to WA5FRF on the day of the WWV Centennial Festival of Frequency Measurement. Visualization here: https://youtu.be/D23DhteWOV0
description: {"references": ["10.1109/LGRS.2021.3063361"]}
DOI: 10.5281/zenodo.4722264
title: Raytrace Simulation Results: WWV → WA9VNJ, SAMI3, 10 MHz, 17 August 2017, Base and Eclipse

description: SAMI3 simulation, with and without the eclipse included in the simulation. You can see the video here: https://www.youtube.com/watch?v=a5QuitNRvcM
DOI: 10.18112/openneuro.ds003487.v1.0.2
title: Wanting and Liking within the Human Ventral Striatum
DOI: 10.18112/openneuro.ds003487.v2.0.0
title: Wanting and Liking within the Human Ventral Striatum
DOI: 10.5281/zenodo.4730672
title: Quantitative meta-analysis data assumptions

description: The proportion and frequency of health service use, aggregated data for meta-analysis from published studies.
DOI: 10.5281/zenodo.4730671
title: Quantitative meta-analysis data assumptions

description: The proportion and frequency of health service use, aggregated data for meta-analysis from published studies.
DOI: 10.5517/ccdc.csd.cc26l7nq
title: CCDC 2043323: Experimental Crystal Structure Determination

description: Related Article: Quan-Guo Zhai, Ying-Ying Xue, Xiao-Ying Bai, Jing Zhang, Ying Wang, Shu-Ni Li, Yu-Cheng Jiang, Man-Cheng Hu|2021|Angew.Chem.,Int.Ed.|60|10122|doi:10.1002/anie.202015861
DOI: 10.5517/ccdc.csd.cc26l7pr
title: CCDC 2043324: Experimental Crystal Structure Determination

description: Related Article: Quan-Guo Zhai, Ying-Ying Xue, Xiao-Ying Bai, Jing Zhang, Ying Wang, Shu-Ni Li, Yu-Cheng Jiang, Man-Cheng Hu|2021|Angew.Chem.,Int.Ed.|60|10122|doi:10.1002/anie.202015861
DOI: 10.5517/ccdc.csd.cc26l7qs
title: CCDC 2043325: Experimental Crystal Structure Determination

description: Related Article: Quan-Guo Zhai, Ying-Ying Xue, Xiao-Ying Bai, Jing Zhang, Ying Wang, Shu-Ni Li, Yu-Cheng Jiang, Man-Cheng Hu|2021|Angew.Chem.,Int.Ed.|60|10122|doi:10.1002/anie.202015861
DOI: 10.5517/ccdc.csd.cc26l7rt
title: CCDC 2043326: Experimental Crystal Structure Determination

description: Related Article: Quan-Guo Zhai, Ying-Ying Xue, Xiao-Ying Bai, Jing Zhang, Ying Wang, Shu-Ni Li, Yu-Cheng Jiang, Man-Cheng Hu|2021|Angew.Chem.,Int.Ed.|60|10122|doi:10.1002/anie.202015861
DOI: 10.5517/ccdc.csd.cc26l7sv
title: CCDC 2043327: Experimental Crystal Structure Determination

description: Related Article: Quan-Guo Zhai, Ying-Ying Xue, Xiao-Ying Bai, Jing Zhang, Ying Wang, Shu-Ni Li, Yu-Cheng Jiang, Man-Cheng Hu|2021|Angew.Chem.,Int.Ed.|60|10122|doi:10.1002/anie.202015861
DOI: 10.5517/ccdc.csd.cc26l7tw
title: CCDC 2043328: Experimental Crystal Structure Determination

description: Related Article: Quan-Guo Zhai, Ying-Ying Xue, Xiao-Ying Bai, Jing Zhang, Ying Wang, Shu-Ni Li, Yu-Cheng Jiang, Man-Cheng Hu|2021|Angew.Chem.,Int.Ed.|60|10122|doi:10.1002/anie.202015861
DOI: 10.5517/ccdc.csd.cc26l7vx
title: CCDC 2043329: Experimental Crystal Structure Determination

description: Related Article: Quan-Guo Zhai, Ying-Ying Xue, Xiao-Ying Bai, Jing Zhang, Ying Wang, Shu-Ni Li, Yu-Cheng Jiang, Man-Cheng Hu|2021|Angew.Chem.,Int.Ed.|60|10122|doi:10.1002/anie.202015861