cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.3pqn28
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen)",
 "TaxonKey is Pelodiscus variegatus"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005921-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/icpsr39559
title: Methods for Heterogeneity of Treatment Effects: Random Forest Counterfactual Machines [Methods Study], Cleveland, Ohio, 2014-2019
title: Archival Version

description: Patients may respond differently to the same treatment due to individual traits such as age or gender. Knowing how different traits can affect a patient's response to treatment can help doctors and patients make better treatment decisions. For example, this information can help doctors know what types of cancer medicines work better for certain patients. This project focuses on improving the methods that researchers use to compare how treatments work for different patients.
In this project, the research team developed and tested a statistical method called random forests, or RF. RF is a way to analyze data using a technique called machine learning. In machine learning, computers use data to learn how to perform different tasks with little or no human input. Many types of RF methods exist. The team compared multiple RF methods to learn how well the methods would work to find out how patients with different traits respond to the same treatment.
 To access the R package, please visit the randomForestSRC CRAN webpage.
description: To develop and evaluate random forest methods for estimating individual treatment effects. Specifically, aim 1 was to develop comprehensive methodology (a) to estimate individual TEs (ITEs) for patients using counterfactual random forest (RF) machines for heterogeneous data, which (b) work across differing magnitudes of HTE, when (c) data are observational with potential confounding, and (d) with survival outcomes and multiple treatment comparisons. Aim 2 was to develop software to implement these new methods in a wide array of comparative effectiveness research applications by adding functionality to the existing CRAN-distributed randomForestSRC package developed by our group, a package in its fifth release at the beginning of this project.
description: Researchers tested multiple RF methods in four studies, including three studies using simulated data sets and one study using empirical data. In the first study using data that simulated randomized controlled trials, they compared RF to other methods of estimating individual treatment effects, including multiple imputation and Bayesian Additive Regression Trees (BART). In the remaining studies, they tested the performance of various RF methods in scenarios varying the magnitude of HTE in randomized trials, using potentially confounded observational data, and accommodating survival outcomes and multiple treatment comparisons.
 An advisory board made up of public health department representatives, infectious disease doctors, and community researchers provided input during the study.
description: Datasets: 
DS1: Methods for Heterogeneity of Treatment Effects: Random Forest Counterfactual Machines [Methods Study], Cleveland, Ohio, 2014-2019
description: Patients who were treated for ischemic cardiomyopathy at the Cleveland Clinic.
DOI: 10.3886/icpsr39559.v1
title: Methods for Heterogeneity of Treatment Effects: Random Forest Counterfactual Machines [Methods Study], Cleveland, Ohio, 2014-2019
title: Version 1

description: Patients may respond differently to the same treatment due to individual traits such as age or gender. Knowing how different traits can affect a patient's response to treatment can help doctors and patients make better treatment decisions. For example, this information can help doctors know what types of cancer medicines work better for certain patients. This project focuses on improving the methods that researchers use to compare how treatments work for different patients.
In this project, the research team developed and tested a statistical method called random forests, or RF. RF is a way to analyze data using a technique called machine learning. In machine learning, computers use data to learn how to perform different tasks with little or no human input. Many types of RF methods exist. The team compared multiple RF methods to learn how well the methods would work to find out how patients with different traits respond to the same treatment.
 To access the R package, please visit the randomForestSRC CRAN webpage.
description: To develop and evaluate random forest methods for estimating individual treatment effects. Specifically, aim 1 was to develop comprehensive methodology (a) to estimate individual TEs (ITEs) for patients using counterfactual random forest (RF) machines for heterogeneous data, which (b) work across differing magnitudes of HTE, when (c) data are observational with potential confounding, and (d) with survival outcomes and multiple treatment comparisons. Aim 2 was to develop software to implement these new methods in a wide array of comparative effectiveness research applications by adding functionality to the existing CRAN-distributed randomForestSRC package developed by our group, a package in its fifth release at the beginning of this project.
description: Researchers tested multiple RF methods in four studies, including three studies using simulated data sets and one study using empirical data. In the first study using data that simulated randomized controlled trials, they compared RF to other methods of estimating individual treatment effects, including multiple imputation and Bayesian Additive Regression Trees (BART). In the remaining studies, they tested the performance of various RF methods in scenarios varying the magnitude of HTE in randomized trials, using potentially confounded observational data, and accommodating survival outcomes and multiple treatment comparisons.
 An advisory board made up of public health department representatives, infectious disease doctors, and community researchers provided input during the study.
description: Datasets: 
DS1: Methods for Heterogeneity of Treatment Effects: Random Forest Counterfactual Machines [Methods Study], Cleveland, Ohio, 2014-2019
description: Patients who were treated for ischemic cardiomyopathy at the Cleveland Clinic.
DOI: 10.15468/dl.qr4xtv
title: Occurrence Download

description: A dataset containing 3322 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Nitella mucronata"
 ]
}

 The dataset includes 3322 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005922-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.10501.61921
title: 20251109132909
DOI: 10.5281/zenodo.17700979
title: sncRNA Annotation GTF

description: Custom annotation GTF file created for GENOME_QUANTIFICATION module of PerSeqPIPE workflow.
DOI: 10.5281/zenodo.17154226
title: sncRNA Annotation GTF

description: Custom annotation GTF file created for GENOME_QUANTIFICATION module of PerSeqPIPE workflow.
DOI: 10.15468/dl.erpkb2
title: Occurrence Download

description: A dataset listing the 4 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-35.78663 -9.5523,-35.75443 -9.60162,-35.74091 -9.6187,-35.73767 -9.63695,-35.7352 -9.6492,-35.73483 -9.65425,-35.73237 -9.65461,-35.73295 -9.63331,-35.73463 -9.61249,-35.74466 -9.59971,-35.74989 -9.59352,-35.78308 -9.55038,-35.78663 -9.5523))",
 "HasGeospatialIssue is false",
 "TaxonKey is Mammalia"
 ]
}

 The dataset's 4 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005919-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17701060
title: Anhang zur Studie "Welche Geschlechtsvorstellungen erzeugen nicht-referenzielle generische Maskulina"

description: Appendix zur experimentellen Studie „Welche Geschlechtsvorstellungen erzeugen nicht-referenzielle (generische) Maskulina? Zum Einfluss von Stereotypen und Grammatik“ (Hannah-Charlotte Bröder, Anne Rosar).

Enthalten sind die Stimuli (Testsätze) sowie ein Überblick über die Klassifizierung der Items von Misersky et al. (2014, Tabelle 3, doi: 10.3758/s13428-013-0409-z) als Berufs- bzw. Rollenbezeichnung.

Die Studie wurde von der Open-access-Zeitschrift Linguistik online im Double-Blind-Peer-Review positiv begutachtet. Die Materialien dienen der Replikation und Nachnutzung und ersetzen den Anhang des Manuskripts.
DOI: 10.15468/dl.r8ec9s
title: Occurrence Download

description: A dataset containing 5664 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Africa, Europe)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sparus aurata"
 ]
}

 The dataset includes 5664 records from 112 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005927-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5yqtg4
title: Occurrence Download

description: A dataset containing 48431 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lepidoptera",
 "Year 1980-2025"
 ]
}

 The dataset includes 48431 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005924-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dvefju
title: Occurrence Download

description: A dataset containing 5775 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is imr_mareano_beamtrawl",
 "TaxonKey is Mollusca"
 ]
}

 The dataset includes 5775 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005929-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dw5jx6
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.28_1",
 "TaxonKey is Ammodendron bifolium"
 ]
}

 The dataset includes 43 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005928-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q9rzs6
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen)",
 "TaxonKey is Platysternon megacephalum"
 ]
}

 The dataset includes 102 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005932-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w9k3ra
title: Occurrence Download

description: A dataset containing 4853 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-122.4322634260575 41.9890209156496, -122.44364715147785 41.986986081762375, -122.45427876739775 41.98333231991981, -122.46374901374054 41.97820038196722, -122.47169362466826 41.971787910579316, -122.47780737716187 41.96434177913905, -122.48185580746998 41.95614853661597, -122.4836841472736 41.94752333500259, -122.48322314758228 41.93879777405652, -122.4804915855147 41.93030713717234, -122.47559538120164 41.92237751205879, -122.46872338331887 41.91531329030626, -122.46014000704331 41.90938552149486, -122.45017502315876 41.90482156150656, -122.43921089812353 41.90179640302786, -122.42766816955466 41.90042601113193, -122.41598940794655 41.90076291088, -122.40462236234703 41.90279418982728, -122.39400291446049 41.90644198901172, -122.38453847189162 41.911566464349434, -122.37659241691057 41.91797110928176, -122.37047019238551 41.92541024193249, -122.36640755186086 41.93359837883366, -122.36456142703139 41.94222114527652, -122.36500377449245 41.95094731223558, -122.36771865675323 41.95944150405639, -122.37260269302924 41.96737709182412, -122.37946888711896 41.974448776189114, -122.38805370742442 41.98038437145672, -122.39802716332642 41.98495533023784, -122.40900549858188 41.98798559434243, -122.42056601219569 41.98935842141128, -122.4322634260575 41.9890209156496))",
 "Year is one of (2019, 2020, 2021, 2022, 2023, 2024, 2025)",
 "KingdomKey is one of (Animalia, Fungi, Plantae)"
 ]
}

 The dataset includes 4853 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005935-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13852366
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.5ep9d6
title: Occurrence Download

description: A dataset containing 651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-122.38012570561074 42.01491771855002, -122.39151666892506 42.01288873128303, -122.40215669560578 42.00924032851481, -122.41163620056766 42.00411305578394, -122.41959056043572 41.997704376348516, -122.42571417612997 41.990261017980465, -122.42977220398134 41.98206942342219, -122.43160950663032 41.973444681853394, -122.43115649113582 41.96471837596798, -122.42843162889926 41.956225818407944, -122.42354058414573 41.94829317122237, -122.41667200905259 41.941224942497534, -122.40809018898649 41.935292335933646, -122.39812483633558 41.93072289321386, -122.38715843260773 41.92769181738386, -122.3756116032039 41.926315300401406, -122.36392707573069 41.92664610209728, -122.3525528197121 41.92867154375217, -122.34192499238677 41.932313990197734, -122.33245132159946 41.93743380269238, -122.32449554252918 41.94383465373183, -122.31836347032161 41.951271007346435, -122.31429123607636 41.95945748720324, -122.31243613994697 41.96807978278862, -122.31287048376626 41.97680668378697, -122.3155786387212 41.985302786955835, -122.3204574841157 41.993241390460085, -122.32732022501514 42.000317079418735, -122.33590346425997 42.00625751437921, -122.34587727341015 42.010833961855695, -122.35685788353545 42.01387015239116, -122.36842250643892 42.01524911535943, -122.38012570561074 42.01491771855002))",
 "Year is one of (2019, 2020, 2021, 2022, 2023, 2024, 2025)",
 "KingdomKey is one of (Animalia, Fungi, Plantae)"
 ]
}

 The dataset includes 651 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005936-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tey4zp
title: Occurrence Download

description: A dataset containing 2407 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-122.04344140387346 42.18379110870292, -122.05487946720145 42.1817999183186, -122.0655741816086 42.17818618321722, -122.07511384876486 42.17308911433473, -122.08313152202274 42.16670501332528, -122.08931916000459 42.159279664129286, -122.09343945297587 42.151098819592995, -122.09533486938125 42.14247715911299, -122.09493358616595 42.133746150952554, -122.09225209391258 42.12524129246757, -122.08739440033979 42.11728922185748, -122.08054788753766 42.110195195975855, -122.07197600425287 42.10423141077795, -122.06200809016859 42.09962660542466, -122.05102673093782 42.09655733975063, -122.0394531280909 42.09514127000433, -122.02773103499818 42.09543267204223, -122.01630985763711 42.09742037724788, -122.00562754627505 42.10102819720882, -121.99609391099153 42.10611782151639, -121.98807498014028 42.11249408188613, -121.98187898656124 42.119912388043744, -121.97774451205608 42.128088059381085, -121.97583124718943 42.13670720407327, -121.97621373227835 42.14543873686245, -121.97887833857935 42.153947080522805, -121.98372362910388 42.161905066269306, -121.99056411001415 42.16900653672333, -121.99913725086849 42.17497816256153, -122.00911352053535 42.17959001095641, -122.0201090613032 42.18266444983348, -122.03170051263052 42.184083035370065, -122.04344140387346 42.18379110870292))",
 "Year is one of (2019, 2020, 2021, 2022, 2023, 2024, 2025)",
 "KingdomKey is one of (Animalia, Fungi, Plantae)"
 ]
}

 The dataset includes 2407 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005937-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5683/sp3/mc0lgm
title: Tableaux symétriques d'entrées-sorties provinciaux, 2022 [Canada]
title: Provincial Symmetric Input-Output Tables, 2022 [Canada]

description: La Division des comptes des industries de Statistique Canada publie annuellement des tableaux provinciaux des ressources et des emplois. Bien que ces tableaux industrie par produit reflètent assez fidèlement les transactions économiques réelles, certains types d’analyse et de modélisation requièrent des tableaux d’entrées-sorties symétriques industrie par industrie. Les tableaux symétriques provinciaux industrie par industrie montrent les transactions interindustrielles, c’est-à-dire tous les achats d’une industrie auprès de toutes les autres industries, y compris les dépenses relatives aux importations et aux sorties de stocks ainsi que toutes les dépenses liées aux intrants primaires. De même, les tableaux symétriques provinciaux de la demande finale montrent tous les achats faits par une catégorie de demande finale auprès de toutes les autres industries, y compris les dépenses relatives aux importations et aux sorties de stocks ainsi que toutes les dépenses liées aux impôts indirects.
&lt;br&gt;
&lt;br&gt;
Ces tableaux sont offerts au niveau détail et aux niveaux d’agrégation Lien-1997, Lien-1961 et Sommaire. Pour connaître l’explication de la méthodologie utilisée, l’utilisateur est invité à communiquer avec la Division des comptes des industries de Statistique Canada.
&lt;br&gt;
description: Le titre de cette série a été changé de la série "Tableaux symétriques d'entrées-sorties provinciaux : niveau d'agrégation S à Tableaux symétriques d'entrées-sorties provinciaux" le 1er avril 2019.
description: Tableaux symétriques d'entrées-sorties provinciaux
DOI: 10.34740/kaggle/ds/7498954
title: Drive&Act
DOI: 10.5281/zenodo.17311870
title: Anhang zur Studie "Welche Geschlechtsvorstellungen erzeugen nicht-referenzielle generische Maskulina"

description: Appendix zur experimentellen Studie „Welche Geschlechtsvorstellungen erzeugen nicht-referenzielle (generische) Maskulina? Zum Einfluss von Stereotypen und Grammatik“ (Hannah-Charlotte Bröder, Anne Rosar).

Enthalten sind die Stimuli (Testsätze) sowie ein Überblick über die Klassifizierung der Items von Misersky et al. (2014, Tabelle 3, doi: 10.3758/s13428-013-0409-z) als Berufs- bzw. Rollenbezeichnung.

Die Studie wurde von der Open-access-Zeitschrift Linguistik online im Double-Blind-Peer-Review positiv begutachtet. Die Materialien dienen der Replikation und Nachnutzung und ersetzen den Anhang des Manuskripts.
DOI: 10.5525/gla.researchdata.2098
title: Self-excited oscillations in a finite-length collapsible channel flow with a heavy wall

description: Data set accompanying `Self-excited oscillations in a finite-length collapsible channel flow with a heavy wall’.
DOI: 10.5281/zenodo.17697843
title: PAMGuard MATLAB R and Python tutorial dataset

description: This dataset is for the PAMGuard MATLAB, R and Python tutorial designed to help users open PAMGuard (www.pamguard.org) data files using MATLAB, R or Python. The tutorial is written in quarto and the source code is located on GitHub.

This dataset accompanies the tutorial and consists of three semi-anonymised datasets.

The zip file contains three folders, each with a PAMBinary sub folder that contains PAMGuard data files. The three datasets are;



LTSA_2 - contains long term spectral average data collected on a 384kHz sample rate multi channel recorder in 2025.

porpoise_data - contains detected transient sounds from a high density porpoise area. Data were recorded on a 10 channel hydrophone array at 500kHz sample rate. 

whistle_data - contains a wav file and detected contours in the PAMGuard binary files. Data were collected form a stereo hydrophone array at 96kHz sample rate. 


These data are open and can be used by any institute, business etc.
DOI: 10.5281/zenodo.17697844
title: PAMGuard MATLAB R and Python tutorial dataset

description: This dataset is for the PAMGuard MATLAB, R and Python tutorial designed to help users open PAMGuard (www.pamguard.org) data files using MATLAB, R or Python. The tutorial is written in quarto and the source code is located on GitHub.

This dataset accompanies the tutorial and consists of three semi-anonymised datasets.

The zip file contains three folders, each with a PAMBinary sub folder that contains PAMGuard data files. The three datasets are;



LTSA_2 - contains long term spectral average data collected on a 384kHz sample rate multi channel recorder in 2025.

porpoise_data - contains detected transient sounds from a high density porpoise area. Data were recorded on a 10 channel hydrophone array at 500kHz sample rate. 

whistle_data - contains a wav file and detected contours in the PAMGuard binary files. Data were collected form a stereo hydrophone array at 96kHz sample rate. 


These data are open and can be used by any institute, business etc.
DOI: 10.5281/zenodo.14046219
title: Data for the paper "Assessing the worth of noble gas tracer concentrations in alluvial river-aquifer systems using data space inversion"

description: This is the modelling data
DOI: 10.5281/zenodo.17698757
title: Data for the paper "Assessing the worth of noble gas tracer concentrations in alluvial river-aquifer systems using data space inversion"

description: This is the modelling data
DOI: 10.5523/bris.v2grnk217jgi2wd8m9kur177f
title: Aspheric lens on pillar paper

description: Data used in published article
DOI: 10.15468/dl.k3e7a3
title: Occurrence Download

description: A dataset listing the 83 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is BatMapPH: Philippine Bat Species Occurrence Database"
 ]
}

 The dataset's 83 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005930-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hj5u74
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((112.74424 -7.75773,112.71568 -8.1457,112.94011 -8.33147,113.25023 -8.29917,113.40121 -8.07298,113.2992 -7.8305,113.10333 -7.76986,112.74424 -7.75773))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chrysocolaptes strictus"
 ]
}

 The dataset includes 11 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005940-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.