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

description: A dataset containing 1669 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 {
 "or" : [
 "DatasetKey is University of Michigan Museum of Zoology, Division of Mollusks",
 "DatasetKey is NMNH Extant Specimen Records (USNM, US)",
 "DatasetKey is Museum of Comparative Zoology, Harvard University",
 "DatasetKey is Auburn University Museum of Natural History Mollusks",
 "DatasetKey is Malacology Collection at the Academy of Natural Sciences of Philadelphia",
 "DatasetKey is NCSM Mollusk Collection",
 "DatasetKey is UF Invertebrate Zoology",
 "DatasetKey is Field Museum of Natural History (Zoology) Invertebrate Collection"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lampsilis teres (Rafinesque, 1820)"
 ]
}

 The dataset includes 1669 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021940-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.76p8pq
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Anisadenia pubescens Griff."
 ]
}

 The dataset includes 75 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032669-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ucvno
title: Occurrence Download

description: A dataset containing 246 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ursus thibetanus G.Cuvier, 1823"
 ]
}

 The dataset includes 246 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003776-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k7y4a5
title: Occurrence Download

description: A dataset containing 3003 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Polygonum aviculare L."
 ]
}

 The dataset includes 3003 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037280-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tjtlsc
title: Occurrence Download

description: A dataset containing 535 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cichla Bloch & Schneider, 1801",
 "Geometry POLYGON((-78.00 -10.00,-78.00 7.46,-50.45 7.46,-50.45 -10.00,-78.00 -10.00))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 535 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003776-160526112335914/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zbv7dr
title: Occurrence Download

description: A dataset containing 18683 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tropidophora Jeffreys, 1882, Tropidophora Thomson, 1858, Tropidopterus Blanchard, 1845, Tropidopterus Gemminger & Harold, 1868, Tropidopholis Fitzinger, 1843, Tropidophora Troschel, 1847, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropidurus Wied-Neuwied, 1824, Tropidurus Wiegmann, 1835, Trapidurus Fitzinger, 1861, Troidurus, Tropiderus Motschulsky, 1875, Tropisurus Diesing, 1835, Tropiocolotes W.Peters, 1880, Tropiocolotes W.Peters, 1880, Tupinambis Daudin, 1802, Tympanocryptis W.C.H.Peters, 1863, Tympanocryptis W.C.H.Peters, 1863, Tympanocryptis W.C.H.Peters, 1863, Tympanocryptis W.C.H.Peters, 1863, Tympanocryptis W.C.H.Peters, 1863, Tympanocryptis W.C.H.Peters, 1863, Underwoodisaurus Wermuth, 1965, Uracentron Kaup, 1826, Urakentron Kaup, 1828, Urocentron Fitzinger, 1843, Uracentron Kaup, 1826, Urakentron Kaup, 1828, Urocentron Fitzinger, 1843, Uranoscodon Kaup, 1825, Uranoscodon Bonaparte, 1832, Uranoscodon Linneaus, 1758, Uraniscodon Kaup, 1826, Uromastyx Merrem, 1820, Uromastix Merrem, 1820, Uromasyx, Uromastyx Merrem, 1820, Uromastix Merrem, 1820, Uromasyx, Uromastyx Merrem, 1820, Uromastix Merrem, 1820, Uromasyx, Urosaurus Hallowell, 1854, Ugrosaurus Cobabe & Fastovsky, 1987, Urosaurus Hallowell, 1854, Ugrosaurus Cobabe & Fastovsky, 1987, Urosaurus Hallowell, 1854)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 18683 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011844-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d9q5w9
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anablepsoides urophthalmus (Günther, 1866)"
 ]
}

 The dataset includes 129 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006537-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lmhhxa
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rubus betonicifolius Focke"
 ]
}

 The dataset includes 17 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003776-171124123535762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g4mw58
title: Occurrence Download

description: A dataset containing 222 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is one of (Cuon alpinus (Pallas, 1811), Ursus thibetanus G, Manis pentadactyla Linnaeus, 1758)"
 ]
}

 The dataset includes 222 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026607-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aqs9fc
title: Occurrence Download

description: A dataset containing 6911 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "TaxonKey is Chromista",
 "Year 2000-2005"
 ]
}

 The dataset includes 6911 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040340-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fqexzg
title: Occurrence Download

description: A dataset containing 2146 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Bixaceae"
 ]
}

 The dataset includes 2146 records from 107 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003776-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2b6yze
title: Occurrence Download

description: A dataset containing 4215 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pastinachus ater (Macleay, 1883)"
 ]
}

 The dataset includes 4215 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029460-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wfialp
title: Occurrence Download

description: A dataset containing 714 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tillandsia juncea (Ruiz & Pav.) Poir."
 ]
}

 The dataset includes 714 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003777-150316153013904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5cut6
title: Occurrence Download

description: A dataset containing 92196 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 {
 "or" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "DatasetKey is BLM - National Landscape Monitoring Framework - Plants",
 "DatasetKey is Intermountain Herbarium (Vasc. & Algae)",
 "DatasetKey is The New York Botanical Garden Herbarium (NY)"
 ]
 },
 "GadmGid is USA.29_1",
 "MediaType is Image",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 92196 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016161-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r8sx33
title: Occurrence Download

description: A dataset containing 433 species occurrences available in GBIF matching the query:
{
 "VerbatimScientificName" : [
 "is baylisascaris"
 ]
}

 The dataset includes 433 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040351-231002084531237/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.25605059.v1
title: Low-frequency electrically induced exercise after spinal cord injury: Physiologic challenge to skeletal muscle and feasibility for long-term use

description: Skeletal muscle has traditionally been considered a “force generator”: necessary for purposes of locomotion, but expendable for non-ambulators who use wheelchairs, such as people with a spinal cord injury (SCI). Active skeletal muscle plays an indispensable role in regulating systemic metabolic functions, even in people with paralysis, but because of severe osteoporosis, high tetanic muscle forces induced with high frequency electrical stimulation may be risky for some individuals. The purpose of this study was to compare the physiologic muscle properties incurred by two low force/low frequency repetitive stimulation protocols (1 and 3 Hz); and, to assess the acceptability of each protocol among people with SCI. Ten individuals with chronic SCI (12.9 years) and 11 individuals without SCI (NonSCI) participated in the study. Participants received either 1 or 3 Hz stimulation to the quadriceps muscle on Day 1, then the converse on Day 2. Each session consisted of 1000 stimulus pulses. The initial and maximum forces were similar for the 1 and 3 Hz frequencies. The fatigue index (FI) for SCI and NonSCI groups were lower (P &lt; 0.007) for 3 Hz than for 1 Hz (0.34 ± 0.17 versus 0.65 ± 0.16 and 0.72 ± 0.14 versus 0.87 ± 0.07, respectively). The 3 Hz stimulation offered the greatest physiological challenge and was perceived as more acceptable for long term use among people with SCI.
DOI: 10.6084/m9.figshare.25605054.v1
title: Credit risk prediction with and without weights of evidence using quantitative learning models

description: The credit risk assessment process is necessary for maintaining financial stability, cost and time efficiency, model performance accuracy, comparability analysis and future business implications in the commercial banking sector. By accurately predicting credit risk, highly regulated banks can make informed lending decisions and minimize potential financial losses. The purpose of this paper is to assess the power of conventional predictive statistical models with and without transforming the features to gain better insights into customer’s creditworthiness. The findings of the predicted performance of the logistics regression model are compared to the performance results of machine learning models for credit risk assessment using commercial banking credit registry data. Each model has its strengths and weaknesses, and where one model lacks, another performs better. The article reveals that simpler credit risk assessment techniques delivered outstanding performance while consuming less processing power and have given insights into the most contributing feature categories. Improving a conventional predictive statistical model using some of the feature transformations reduces the overall model performance, specifically for credit registry data. The logistics regression model outperformed all models with the highest F1, accuracy, Jaccard Index and AUC values, respectively. Financial institutions, specifically banks have questioned whether transformations using Weights of Evidence (WoE) have been significant in quantifying the relationship between categorical independent variables for various types of credit data. This study provides insights when considering the usage of feature transformation for credit risk modelling in commercial banking. The transformation technique is particularly useful in situations where statistical predictive modelling techniques are employed. The results revealed that not only can the logistic regression models perform similarly to the machine learning models but can also outperform them. The best performance is attributed to the simplicity, interpretability, and access to understanding features of individual clients within a portfolio of credit products. The logistic regression model without transformation turned out to perform the best out of the five machine learning models. Considering the business impact, enhancing the logistic regression model by using a WoE transformation did not improve the model's performance for commercial banking data considered. However, the transformation did provide insights regarding each binned categorical independent variable. Therefore, our findings in this article contribute towards assisting banks in managing the impact and interpretability of each binned feature category on the discriminatory power of credit scoring.
DOI: 10.6084/m9.figshare.25605054
title: Credit risk prediction with and without weights of evidence using quantitative learning models

description: The credit risk assessment process is necessary for maintaining financial stability, cost and time efficiency, model performance accuracy, comparability analysis and future business implications in the commercial banking sector. By accurately predicting credit risk, highly regulated banks can make informed lending decisions and minimize potential financial losses. The purpose of this paper is to assess the power of conventional predictive statistical models with and without transforming the features to gain better insights into customer’s creditworthiness. The findings of the predicted performance of the logistics regression model are compared to the performance results of machine learning models for credit risk assessment using commercial banking credit registry data. Each model has its strengths and weaknesses, and where one model lacks, another performs better. The article reveals that simpler credit risk assessment techniques delivered outstanding performance while consuming less processing power and have given insights into the most contributing feature categories. Improving a conventional predictive statistical model using some of the feature transformations reduces the overall model performance, specifically for credit registry data. The logistics regression model outperformed all models with the highest F1, accuracy, Jaccard Index and AUC values, respectively. Financial institutions, specifically banks have questioned whether transformations using Weights of Evidence (WoE) have been significant in quantifying the relationship between categorical independent variables for various types of credit data. This study provides insights when considering the usage of feature transformation for credit risk modelling in commercial banking. The transformation technique is particularly useful in situations where statistical predictive modelling techniques are employed. The results revealed that not only can the logistic regression models perform similarly to the machine learning models but can also outperform them. The best performance is attributed to the simplicity, interpretability, and access to understanding features of individual clients within a portfolio of credit products. The logistic regression model without transformation turned out to perform the best out of the five machine learning models. Considering the business impact, enhancing the logistic regression model by using a WoE transformation did not improve the model's performance for commercial banking data considered. However, the transformation did provide insights regarding each binned categorical independent variable. Therefore, our findings in this article contribute towards assisting banks in managing the impact and interpretability of each binned feature category on the discriminatory power of credit scoring.
DOI: 10.15468/dl.h2eesq
title: Occurrence Download

description: A dataset containing 43488 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "TaxonKey is Fungi",
 "Year 2000-2005"
 ]
}

 The dataset includes 43488 records from 185 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040355-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-237783
title: Holy convocation, Northern California (50th: 1996), Women's day program

description: [description english/roman)] 50th Holy convocation, Women's day program, "Holy women: our responsibility to God's work", Northern California, Berkeley, California, 1996 June 7.
DOI: 10.15468/dl.j299qw
title: Occurrence Download

description: A dataset containing 109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium salzmannii Delile",
 "HasCoordinate is true",
 "Year is greater than or equal to 1900",
 "BasisOfRecord is one of (Human Observation, Specimen, Unknown evidence)"
 ]
}

 The dataset includes 109 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082185-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fzkmuz
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Parupeneus procerigena Kim & Amaoka, 2001"
 ]
}

 The dataset includes 25 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064994-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mds98x
title: Occurrence Download

description: A dataset containing 34762 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Emys orbicularis (Linnaeus, 1758)"
 ]
}

 The dataset includes 34762 records from 503 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082196-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-237840
title: Annual state convocation, Texas southwest, COGIC, Waco, Women's day program, 1997

description: [description english/roman)] Annual state convocation, Women's day program, "Church of God in Christ women looking back with praises: moving forward with hope", Texas southwest, Church of God in Christ, State Temple, Waco, Texas, 1997 July 12.
DOI: 10.15468/dl.cjtqge
title: Occurrence Download

description: A dataset containing 202489 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Olea europaea L."
 ]
}

 The dataset includes 202489 records from 249 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0073190-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d9x88w
title: Occurrence Download

description: A dataset containing 10957 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gentiana clusii E.P.Perrier & Songeon",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "Year is greater than or equal to 1990",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 10957 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0163457-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nn69p8
title: Occurrence Download

description: A dataset containing 7368 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Senecio angulatus L.fil."
 ]
}

 The dataset includes 7368 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005028-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aeqzv3
title: Occurrence Download

description: A dataset containing 220425 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aechmophorus clarkii (Lawrence, 1858)"
 ]
}

 The dataset includes 220425 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014901-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.