cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31097518
title: Additional file 2 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 2. Table of results for High power set without clinical data with 5-fold cross validation with patient split.
DOI: 10.6084/m9.figshare.31097518.v1
title: Additional file 2 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 2. Table of results for High power set without clinical data with 5-fold cross validation with patient split.
DOI: 10.6084/m9.figshare.31097521
title: Additional file 3 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 3. Table of results for Medium power set with 5-fold cross validation with patient split.
DOI: 10.6084/m9.figshare.31097521.v1
title: Additional file 3 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 3. Table of results for Medium power set with 5-fold cross validation with patient split.
DOI: 10.6084/m9.figshare.31097524
title: Additional file 4 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 4. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097524.v1
title: Additional file 4 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 4. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097527
title: Additional file 5 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 5. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097527.v1
title: Additional file 5 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 5. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097530
title: Additional file 6 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 6. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097530.v1
title: Additional file 6 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 6. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097533
title: Additional file 7 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 7. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097533.v1
title: Additional file 7 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 7. Table of results for High power set with 5-fold cross validation with patient split with a new, separate test set of patients.
DOI: 10.6084/m9.figshare.31097536
title: Additional file 8 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 8. Tables of results for clinical data only with cross validation with only one image with only one clinical data for every patient.
DOI: 10.6084/m9.figshare.31097536.v1
title: Additional file 8 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 8. Tables of results for clinical data only with cross validation with only one image with only one clinical data for every patient.
DOI: 10.6084/m9.figshare.31097542
title: Additional file 10 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 10. Table of results for clinical data only with cross validation with patient split after ablation of the age feature.
DOI: 10.6084/m9.figshare.31097542.v1
title: Additional file 10 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 10. Table of results for clinical data only with cross validation with patient split after ablation of the age feature.
DOI: 10.6084/m9.figshare.31097545
title: Additional file 11 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 11. Table of results for clinical data only with cross validation with patient split after ablation of the Anterior gingiva feature.
DOI: 10.6084/m9.figshare.31097545.v1
title: Additional file 11 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 11. Table of results for clinical data only with cross validation with patient split after ablation of the Anterior gingiva feature.
DOI: 10.6084/m9.figshare.31097548
title: Additional file 12 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 12. Table of results for clinical data only with cross validation with patient split after ablation of the Age and Anterior gingiva feature.
DOI: 10.6084/m9.figshare.31097548.v1
title: Additional file 12 of Texture-based image feature analysis for the classification of oral squamous cell carcinoma using machine learning approach

description: Additional file 12. Table of results for clinical data only with cross validation with patient split after ablation of the Age and Anterior gingiva feature.
DOI: 10.6084/m9.figshare.31097562
title: Additional file 2 of Colletotrichum: a versatile fungal genus with diverse infection strategies, host interactions, and management challenges

description: Additional file 2: Table S1. Overview of Colletotrichum species exhibiting mutualistic or endophytic interactions: hosts, benefits, and proposed mechanisms.
DOI: 10.6084/m9.figshare.31097562.v1
title: Additional file 2 of Colletotrichum: a versatile fungal genus with diverse infection strategies, host interactions, and management challenges

description: Additional file 2: Table S1. Overview of Colletotrichum species exhibiting mutualistic or endophytic interactions: hosts, benefits, and proposed mechanisms.
DOI: 10.5281/zenodo.18314377
title: Solanum elaeagnifolium var. leprosum (Ortega) Dunal. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:55
DOI: 10.5281/zenodo.18314378
title: Solanum elaeagnifolium var. leprosum (Ortega) Dunal. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:55
DOI: 10.5281/zenodo.17940364
title: Testate amoeba data from Lakkasuo peatland water level drawdown experiment

description: We investigated the impacts of persistent drying and associated changes in peatland ecosystems to testate amoeba taxonomic composition and functional traits. We collected testate amoebae samples (top 3 cm of dominant mosses) from a water level drawdown experiment situated in Lakkasuo peatland, Finland in 2022. The experiment has been ongoing since 2001-2002 and it has caused vegetation succession mediated by site fertility: the poorest site, ombrotrophic bog, has changed only little, while the richest (mesotrophic fen) and intermediate (oligotrophic fen) have grown tree stands. Testate amoebae were identified, and test width, test length, and aperture size were measured using a light microscope. Categorical traits (test material, test compression, mixotrophy, aperture position) were converted to binary format, assigning a value of 1 if a taxon exhibited the trait and 0 if it did not. Community-weighted mean was calculated for each trait in each plot by quantifying the mean trait value of the taxon present in the community, weighted by their relative abundance.
DOI: 10.5281/zenodo.17940365
title: Testate amoeba data from Lakkasuo peatland water level drawdown experiment

description: We investigated the impacts of persistent drying and associated changes in peatland ecosystems to testate amoeba taxonomic composition and functional traits. We collected testate amoebae samples (top 3 cm of dominant mosses) from a water level drawdown experiment situated in Lakkasuo peatland, Finland in 2022. The experiment has been ongoing since 2001-2002 and it has caused vegetation succession mediated by site fertility: the poorest site, ombrotrophic bog, has changed only little, while the richest (mesotrophic fen) and intermediate (oligotrophic fen) have grown tree stands. Testate amoebae were identified, and test width, test length, and aperture size were measured using a light microscope. Categorical traits (test material, test compression, mixotrophy, aperture position) were converted to binary format, assigning a value of 1 if a taxon exhibited the trait and 0 if it did not. Community-weighted mean was calculated for each trait in each plot by quantifying the mean trait value of the taxon present in the community, weighted by their relative abundance.
DOI: 10.6084/m9.figshare.31097601
title: Additional file 1 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 1: Differentially abundant protein groups, phosphopeptides and transcripts in NST vs ILC at FDR&lt;0.05 and absolute log2 Fold Change &gt;1.
DOI: 10.6084/m9.figshare.31097601.v1
title: Additional file 1 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 1: Differentially abundant protein groups, phosphopeptides and transcripts in NST vs ILC at FDR&lt;0.05 and absolute log2 Fold Change &gt;1.
DOI: 10.6084/m9.figshare.31097604
title: Additional file 2 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 2: Summary of univariable and multivariable Cox analysis based on RFS and OS for features identified in the MOFA model and associated with lymph node involvement.
DOI: 10.6084/m9.figshare.31097604.v1
title: Additional file 2 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 2: Summary of univariable and multivariable Cox analysis based on RFS and OS for features identified in the MOFA model and associated with lymph node involvement.
DOI: 10.6084/m9.figshare.31097607
title: Additional file 3 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 3: Summary of univariable and multivariable Cox analysis based on DRFS and OS for features identified in differential expression analysis and associated with distant metastasis.
DOI: 10.6084/m9.figshare.31097607.v1
title: Additional file 3 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 3: Summary of univariable and multivariable Cox analysis based on DRFS and OS for features identified in differential expression analysis and associated with distant metastasis.
DOI: 10.6084/m9.figshare.31097610
title: Additional file 4 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 4: Summary of univariable and multivariable Cox analysis based on DRFS and OS for features selected in MOFA model and associated with distant metastasis.
DOI: 10.6084/m9.figshare.31097610.v1
title: Additional file 4 of Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

description: Supplementary Table 4: Summary of univariable and multivariable Cox analysis based on DRFS and OS for features selected in MOFA model and associated with distant metastasis.
DOI: 10.5281/zenodo.18314387
title: Solanum flagellare Sendtn. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:55
DOI: 10.5281/zenodo.18314388
title: Solanum flagellare Sendtn. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:55
DOI: 10.34740/kaggle/dsv/11878801
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.brdsmy
title: Occurrence Download

description: A dataset containing 145 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, Nepal, China, Bhutan)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Roscoea purpurea Sm."
 ]
}

 The dataset includes 145 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012759-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.erdzyw
title: Occurrence Download

description: A dataset containing 424 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dianthus barbatus",
 "Country is Poland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 424 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048933-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ybc48n
title: Occurrence Download

description: A dataset containing 198 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Opuntia stricta",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 198 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024419-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.smpu3b
title: Occurrence Download

description: A dataset containing 12629 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tapirus terrestris (Linnaeus, 1758)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12629 records from 123 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003650-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xk7j5a
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rottboellia cochinchinensis (Lour.) Clayton",
 "Country is Gambia"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009583-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bh2tys
title: Occurrence Download

description: A dataset containing 28190 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sphyrna lewini (Griffith & Smith, 1834)"
 ]
}

 The dataset includes 28190 records from 262 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009582-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uf695p
title: Occurrence Download

description: A dataset containing 516 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Potamotrygon magdalenae (Duméril, 1865)"
 ]
}

 The dataset includes 516 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009585-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc110813691
title: Roman Brick Fragment with Partial Stamp, BMC T.138

description: [Text Description:] Imperial (Roman) ❧ [Text or Publication Number Note:] BMC T.138 ❧ [Medium:] Clay ❧ [Script Note:] Latin ❧ [Physical Object Description:] Brick Fragment with Partial Stamp ❧ [Physical Object Note:] 1 1/8 x 4 13/16 x 1 1/8 in. (2.9 x 12.2 x 2.9 cm)
DOI: 10.25549/inscriptifact-ouc110813695
title: Roman Brick Fragment with Partial Stamp, BMC T.138

description: [Text Description:] Imperial (Roman) ❧ [Text or Publication Number Note:] BMC T.138 ❧ [Medium:] Clay ❧ [Script Note:] Latin ❧ [Physical Object Description:] Brick Fragment with Partial Stamp ❧ [Physical Object Note:] 1 1/8 x 4 13/16 x 1 1/8 in. (2.9 x 12.2 x 2.9 cm)
DOI: 10.25549/inscriptifact-ouc110813650
title: Roman Brick Fragment with Partial Stamp, BMC T.138

description: [Text Description:] Imperial (Roman) ❧ [Text or Publication Number Note:] BMC T.138 ❧ [Medium:] Clay ❧ [Script Note:] Latin ❧ [Physical Object Description:] Brick Fragment with Partial Stamp ❧ [Physical Object Note:] 1 1/8 x 4 13/16 x 1 1/8 in. (2.9 x 12.2 x 2.9 cm)
DOI: 10.25549/inscriptifact-ouc110813720
title: Copper Scroll

description: [Text Description:] ❧ list of buried treasure ❧ [Text or Publication Number Note:] 3Q15 Copper Scroll ❧ [Excavation Description:] Found during survey of cliffs at Qumran in March 1952 by Roland de Vaux and William Reed. ❧ [Medium:] Metal ❧ [Script Note:] Jewish ❧ [Physical Object Description:] 23 oxydized copper half-cylinder segments with incised letters
DOI: 10.25549/inscriptifact-ouc110813677
title: Roman Brick Fragment with Partial Stamp, BMC T.138

description: [Text Description:] Imperial (Roman) ❧ [Text or Publication Number Note:] BMC T.138 ❧ [Medium:] Clay ❧ [Script Note:] Latin ❧ [Physical Object Description:] Brick Fragment with Partial Stamp ❧ [Physical Object Note:] 1 1/8 x 4 13/16 x 1 1/8 in. (2.9 x 12.2 x 2.9 cm)
DOI: 10.25549/inscriptifact-ouc110813534
title: Neo-Assyrian Stamp Seal with Multi-figured Scene, BMC S.114

description: [Text Description:] Neo-Assyrian ❧ [Text or Publication Number Note:] BMC S.114 ❧ [Medium:] Stone ❧ [Script Note:] Non-Text ❧ [Physical Object Description:] Stone Stamp Seal ❧ [Physical Object Note:] 1 x 23/32 x 3/4 in. (2.5 x 1.8 x 1.9 cm)
DOI: 10.25549/inscriptifact-ouc110813529
title: Roman Female Head from Palmyrene Funerary Relief, BMC S.88

description: [Text Description:] Imperial (Roman) ❧ [Text or Publication Number Note:] BMC S.88 ❧ [Medium:] Stone ❧ [Script Note:] Non-Text ❧ [Physical Object Description:] Limestone Female Head from Funerary Relief ❧ [Physical Object Note:] 5 11/16 in. x 4 1/2 in. x 4 1/4 in. (14.5 cm x 11.5 cm x 10.8 cm)
DOI: 10.6084/m9.figshare.29123420
title: all_genes_expression_of_diapause_silkworm

description: These tables show the gene expression patterns (fpkm)of diapause silkworm embryos and larvae that were congenitally infected with N. bombycis, and the gene expression patterns of N. bombycis in diapause silkworm embryos and larvae.
DOI: 10.5281/zenodo.17665721
title: Extended data integration of gamification in teacher training: bibliometric analysis, evolutionary trajectories and emerging trends in the era of generative artificial intelligence
DOI: 10.5281/zenodo.17665722
title: Extended data integration of gamification in teacher training: bibliometric analysis, evolutionary trajectories and emerging trends in the era of generative artificial intelligence
DOI: 10.15468/dl.w9cv9s
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Mexico",
 "GadmGid is MEX.30_1",
 "Geometry POLYGON((-102.10000 18.02161,-91.77656 18.02161,-91.77656 22.14901,-102.10000 22.14901,-102.10000 18.02161))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Bassariscus astutus",
 "Year 2015-2025"
 ]
}

 The dataset includes 37 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001383-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nxkgb2
title: Occurrence Download

description: A dataset containing 8071 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dascyllus trimaculatus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8071 records from 127 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001384-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.