cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28748829
title: Application of an interpretable machine learning method to predict the risk of death during hospitalization in patients with acute myocardial infarction combined with diabetes mellitus

description: Predicting the prognosis of patients with acute myocardial infarction (AMI) combined with diabetes mellitus (DM) is crucial due to high in-hospital mortality rates. This study aims to develop and validate a mortality risk prediction model for these patients by interpretable machine learning (ML) methods. Data were sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.2). Predictors were selected by Least absolute shrinkage and selection operator (LASSO) regression and checked for multicollinearity with Spearman’s correlation. Patients were randomly assigned to training and validation sets in an 8:2 ratio. Seven ML algorithms were used to construct models in the training set. Model performance was evaluated in the validation set using metrics such as area under the curve (AUC) with 95% confidence interval (CI), calibration curves, precision, recall, F1 score, accuracy, negative predictive value (NPV), and positive predictive value (PPV). The significance of differences in predictive performance among models was assessed utilising the permutation test, and 10-fold cross-validation further validated the model’s performance. SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) were applied to interpret the models. The study included 2,828 patients with AMI combined with DM. Nineteen predictors were identified through LASSO regression and Spearman’s correlation. The Random Forest (RF) model was demonstrated the best performance, with an AUC of 0.823 (95% CI: 0.774–0.872), high precision (0.867), accuracy (0.873), and PPV (0.867). The RF model showed significant differences (<i>p</i> &lt; 0.05) compared to the K-Nearest Neighbours and Decision Tree models. Calibration curves indicated that the RF model’s predicted risk aligned well with actual outcomes. 10-fold cross-validation confirmed the superior performance of RF model, with an average AUC of 0.828 (95% CI: 0.800–0.842). Significant Variables in RF model indicated that the top eight significant predictors were urine output, maximum anion gap, maximum urea nitrogen, age, minimum pH, maximum international normalised ratio (INR), mean respiratory rate, and mean systolic blood pressure. This study demonstrates the potential of ML methods, particularly the RF model, in predicting in-hospital mortality risk for AMI patients with DM. The SHAP and LIME methods enhance the interpretability of ML models.
DOI: 10.6084/m9.figshare.28748829.v1
title: Application of an interpretable machine learning method to predict the risk of death during hospitalization in patients with acute myocardial infarction combined with diabetes mellitus

description: Predicting the prognosis of patients with acute myocardial infarction (AMI) combined with diabetes mellitus (DM) is crucial due to high in-hospital mortality rates. This study aims to develop and validate a mortality risk prediction model for these patients by interpretable machine learning (ML) methods. Data were sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.2). Predictors were selected by Least absolute shrinkage and selection operator (LASSO) regression and checked for multicollinearity with Spearman’s correlation. Patients were randomly assigned to training and validation sets in an 8:2 ratio. Seven ML algorithms were used to construct models in the training set. Model performance was evaluated in the validation set using metrics such as area under the curve (AUC) with 95% confidence interval (CI), calibration curves, precision, recall, F1 score, accuracy, negative predictive value (NPV), and positive predictive value (PPV). The significance of differences in predictive performance among models was assessed utilising the permutation test, and 10-fold cross-validation further validated the model’s performance. SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) were applied to interpret the models. The study included 2,828 patients with AMI combined with DM. Nineteen predictors were identified through LASSO regression and Spearman’s correlation. The Random Forest (RF) model was demonstrated the best performance, with an AUC of 0.823 (95% CI: 0.774–0.872), high precision (0.867), accuracy (0.873), and PPV (0.867). The RF model showed significant differences (<i>p</i> &lt; 0.05) compared to the K-Nearest Neighbours and Decision Tree models. Calibration curves indicated that the RF model’s predicted risk aligned well with actual outcomes. 10-fold cross-validation confirmed the superior performance of RF model, with an average AUC of 0.828 (95% CI: 0.800–0.842). Significant Variables in RF model indicated that the top eight significant predictors were urine output, maximum anion gap, maximum urea nitrogen, age, minimum pH, maximum international normalised ratio (INR), mean respiratory rate, and mean systolic blood pressure. This study demonstrates the potential of ML methods, particularly the RF model, in predicting in-hospital mortality risk for AMI patients with DM. The SHAP and LIME methods enhance the interpretability of ML models.
DOI: 10.6084/m9.figshare.29152172
title: Electronic Supplementary Material - Reverse taxonomy

description: <b>Electronic Supplementary Materials</b><b> </b>for the article.<b>Supplementary Material 1. </b>List of sampling sites and their detailed characteristics processed using DNA barcoding in this study. (Supplementary Material 1.xlsx)<b>Supplementary Material 2. </b>List of BINs and their taxonomic identification via BOLD database within the five studied insect orders. (Supplementary Material 2.xlsx)
DOI: 10.6084/m9.figshare.29152172.v2
title: Electronic Supplementary Material - Reverse taxonomy

description: <b>Electronic Supplementary Materials</b><b> </b>for the article.<b>Supplementary Material 1. </b>List of sampling sites and their detailed characteristics processed using DNA barcoding in this study. (Supplementary Material 1.xlsx)<b>Supplementary Material 2. </b>List of BINs and their taxonomic identification via BOLD database within the five studied insect orders. (Supplementary Material 2.xlsx)
DOI: 10.6084/m9.figshare.29152172.v1
title: Electronic Supplementary Material - Reverse taxonomy

description: <b>Electronic Supplementary Materials</b><b> </b>for the article.<b>Supplementary Material 1. </b>List of sampling sites and their detailed characteristics processed using DNA barcoding in this study. (Supplementary Material 1.xlsx)<b>Supplementary Material 2. </b>List of BINs and their taxonomic identification via BOLD database within the five studied insect orders. (Supplementary Material 2.xlsx)
DOI: 10.15468/dl.sy6m7u
title: Occurrence Download

description: A dataset containing 2241 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((15.31607 47.13643,15.33675 47.13627,15.32912 47.16556,15.3384 47.18112,15.3486 47.18764,15.35117 47.19934,15.32399 47.19343,15.31326 47.15516,15.31607 47.13643))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2241 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035924-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrvcfx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerophrys gutturalis (Power, 1927)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((25.5395 -23.2724,25.1306 -24.0715,25.5395 -24.0715,25.5395 -23.2724))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035923-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15639747
title: Social Presence in AI Storytelling: The Role of Nonverbal Cues in Engaging Young Learners
DOI: 10.5281/zenodo.15639748
title: Social Presence in AI Storytelling: The Role of Nonverbal Cues in Engaging Young Learners
DOI: 10.5281/zenodo.14040587
title: Enhanced Ionic Conductivity and Electrochemical Properties of Li2B12H12/ZrO2 Nanocomposites for All-Solid-State Lithium Metal Batteries

description: This data repository contains the raw data used in the research article: https://doi.org/10.1021/acsami.5c01939

"Enhanced Ionic Conductivity and Electrochemical Properties of Li2B12H12/ZrO2 Nanocomposites for All-Solid-State Lithium Metal Batteries"
DOI: 10.5281/zenodo.14040588
title: Enhanced Ionic Conductivity and Electrochemical Properties of Li2B12H12/ZrO2 Nanocomposites for All-Solid-State Lithium Metal Batteries

description: This data repository contains the raw data used in the research article: https://doi.org/10.1021/acsami.5c01939

"Enhanced Ionic Conductivity and Electrochemical Properties of Li2B12H12/ZrO2 Nanocomposites for All-Solid-State Lithium Metal Batteries"
DOI: 10.5281/zenodo.15487882
title: Data related to 'The seismic signature of the Atlantis Massif oceanic detachment fault determined from crystallographic preferred orientation and microstructure'

description: Synchrotron and neutron diffraction data of mafic and ultramafic rocks drilled during IODP Expedition 357 related to 'The seismic signature of the Atlantis Massif oceanic detachment fault determined from crystallographic preferred orientation and microstructure'.
DOI: 10.5281/zenodo.15487883
title: Data related to 'The seismic signature of the Atlantis Massif oceanic detachment fault determined from crystallographic preferred orientation and microstructure'

description: Synchrotron and neutron diffraction data of mafic and ultramafic rocks drilled during IODP Expedition 357 related to 'The seismic signature of the Atlantis Massif oceanic detachment fault determined from crystallographic preferred orientation and microstructure'.
DOI: 10.15468/dl.6a6yxd
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerophrys gutturalis (Power, 1927)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.2855 -34.7533,20.509 -34.5676,20.509 -32.9007,17.7723 -32.9007,17.8156 -33.0786,18.3471 -33.7176,18.3748 -33.8287,18.2181 -34.0492,18.3197 -34.3408,18.4452 -34.429,18.5435 -34.4213,18.5872 -34.3667,18.5363 -34.167,18.7345 -34.1508,18.7216 -34.3637,18.7808 -34.4521,19.0289 -34.4206,19.0831 -34.4835,19.2655 -34.5017,19.2032 -34.6157,19.2394 -34.6926,19.375 -34.6963,19.6091 -34.8524,19.8251 -34.8396,19.9798 -34.9064,20.1081 -34.8731,20.1517 -34.7847,20.2855 -34.7533))"
 ]
}

 The dataset includes 30 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035925-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.896k99
title: Occurrence Download

description: A dataset containing 2751134 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 3.0-1000000.0",
 "Country is New Zealand",
 "GbifRegion is Oceania",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1989-2025"
 ]
}

 The dataset includes 2751134 records from 234 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035909-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9m7abg
title: Occurrence Download

description: A dataset containing 24442 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Salvia pratensis L.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 24442 records from 136 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003504-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qcc92y
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Selago caerulea Rolfe"
 ]
}

 The dataset includes 45 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0122781-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2bbppc
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Erysimum horizontale P.Candargy"
 ]
}

 The dataset includes 20 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0154421-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.44hvzf
title: Occurrence Download

description: A dataset containing 16349 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Canna indica L."
 ]
}

 The dataset includes 16349 records from 385 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051071-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jzj7cr
title: Occurrence Download

description: A dataset containing 54 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Senecio pattersonensis Hoover"
 ]
}

 The dataset includes 54 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0124228-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j5vb7r
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Erysimum korabense Kümmerle & Javorka"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0154381-220831081235567/datasets/export for details.
DOI: 10.15468/dl.z5sgj8
title: Occurrence Download

description: A dataset containing 19481 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Plantae",
 "Year 2020-2020"
 ]
}

 The dataset includes 19481 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060386-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dxxe5f
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lophospermum breedlovei Elisens"
 ]
}

 The dataset includes 37 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013261-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.28c5xy
title: Occurrence Download

description: A dataset containing 6136 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Base de datos de la Sala de Colecciones Biológicas de la Universidad Católica del Norte (SCBUCN) Chile"
 ]
}

 The dataset includes 6136 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010091-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xkdwwp
title: Occurrence Download

description: A dataset containing 262 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Westringia senifolia F.Muell."
 ]
}

 The dataset includes 262 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005976-240425142415019/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.icenv8
title: Occurrence Download

description: A dataset containing 4717 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Weddell Sea macrozoobenthos EASIZ I"
 ]
}

 The dataset includes 4717 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007433-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5bhwq
title: Occurrence Download

description: A dataset containing 33844 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Triaenodon obesus (Rüppell, 1837)"
 ]
}

 The dataset includes 33844 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007433-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kapgzh
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vernonia shabaensis Kalanda"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029432-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mmetxz
title: Occurrence Download

description: A dataset containing 123 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Parolinia ornata Webb"
 ]
}

 The dataset includes 123 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013249-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eplxk6
title: Occurrence Download

description: A dataset containing 1118 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Issue is Zero coordinate",
 "Issue is Coordinate out of range",
 "Issue is Coordinate invalid",
 "Issue is Coordinate rounded",
 "Issue is Geodetic datum invalid",
 "Issue is Geodetic datum assumed WGS84",
 "Issue is Coordinate reprojected",
 "Issue is Coordinate reprojection failed",
 "Issue is Coordinate reprojection suspicious",
 "Issue is Coordinate accuracy invalid",
 "Issue is Coordinate precision invalid",
 "Issue is Coordinate uncertainty meters invalid",
 "Issue is Coordinate precision/uncertainty mismatch",
 "Issue is Country coordinate mismatch",
 "Issue is Country mismatch",
 "Issue is Country invalid",
 "Issue is Country derived from coordinates",
 "Issue is Continent country mismatch",
 "Issue is Continent invalid",
 "Issue is Continent derived from coordinates",
 "Issue is Presumed swapped coordinate",
 "Issue is Presumed negated longitude",
 "Issue is Presumed negated latitude",
 "Issue is Recorded date mismatch",
 "Issue is Recorded date invalid",
 "Issue is Recorded date unlikely",
 "Issue is Taxon match fuzzy",
 "Issue is Taxon match higher rank",
 "Issue is Taxon match none",
 "Issue is Depth not metric",
 "Issue is Depth unlikely",
 "Issue is Depth min max swapped",
 "Issue is Depth non numeric",
 "Issue is Elevation unlikely",
 "Issue is Elevation min max swapped",
 "Issue is Elevation not metric",
 "Issue is Elevation non numeric",
 "Issue is Modified date invalid",
 "Issue is Modified date unlikely",
 "Issue is Identified date unlikely",
 "Issue is Identified date invalid",
 "Issue is Basis of record invalid",
 "Issue is Type status invalid",
 "Issue is Multimedia date invalid",
 "Issue is Multimedia URI invalid",
 "Issue is References URI invalid",
 "Issue is Individual count invalid"
 ]
 },
 "TaxonKey is Drosera pygmaea DC."
 ]
}

 The dataset includes 1118 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007433-190320150433242/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j3z5hd
title: Occurrence Download

description: A dataset listing the 1719 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-76.88763 1.17899,-76.79368 1.04502,-76.56065 1.23776,-76.6085 1.49265,-76.89818 1.30562,-76.88763 1.17899))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 1719 records were derived from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0188859-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2uy8wq
title: Occurrence Download

description: A dataset containing 1364 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lophospermum erubescens D.Don ex Sweet"
 ]
}

 The dataset includes 1364 records from 143 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013263-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mhgzf4
title: Occurrence Download

description: A dataset containing 25184 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Year 1998-2019",
 {
 "or" : [
 "InstitutionCode is clo",
 "InstitutionCode is dmns",
 "InstitutionCode is borror laboratory of bioacoustics, ohio state university, columbus, oh (blb)",
 "InstitutionCode is psm",
 "InstitutionCode is ntsrv",
 "InstitutionCode is msb",
 "InstitutionCode is uwbm",
 "InstitutionCode is prbo",
 "InstitutionCode is uam"
 ]
 },
 "TaxonKey is Leucosticte tephrocotis (Swainson, 1832)"
 ]
}

 The dataset includes 25184 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007433-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qn3zh5
title: Occurrence Download

description: A dataset containing 9542002 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China"
 ]
}

 The dataset includes 9542002 records from 4847 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022430-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.