cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30423583
title: Additional file 8 of Splenomegaly in de novo acute myeloid leukemia is associated with ASXL1 mutations together with a distinct clinical and gene expression profile

description: Supplementary Material 8: Table 5.
DOI: 10.6084/m9.figshare.30423583.v1
title: Additional file 8 of Splenomegaly in de novo acute myeloid leukemia is associated with ASXL1 mutations together with a distinct clinical and gene expression profile

description: Supplementary Material 8: Table 5.
DOI: 10.6084/m9.figshare.30423586
title: Additional file 9 of Splenomegaly in de novo acute myeloid leukemia is associated with ASXL1 mutations together with a distinct clinical and gene expression profile

description: Supplementary Material 9: Table 6.
DOI: 10.6084/m9.figshare.30423586.v1
title: Additional file 9 of Splenomegaly in de novo acute myeloid leukemia is associated with ASXL1 mutations together with a distinct clinical and gene expression profile

description: Supplementary Material 9: Table 6.
DOI: 10.15468/dl.fpk5de
title: Occurrence Download

description: A dataset containing 141 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Ailuropoda melanoleuca"
 ]
}

 The dataset includes 141 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051571-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kd8j65
title: Occurrence Download

description: A dataset containing 135 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Celosia nitida"
 ]
}

 The dataset includes 135 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051572-251009101135966/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.30423612
title: Additional file 1 of A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome

description: Additional file 1: Table S1. SpliceAI predictions and experimental splice data used to inform strengths for GT-AG +/-1,2 dinucleotide splice site variants in the TP53 VCEP Specifications v2 (.xls).
DOI: 10.6084/m9.figshare.30423612.v1
title: Additional file 1 of A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome

description: Additional file 1: Table S1. SpliceAI predictions and experimental splice data used to inform strengths for GT-AG +/-1,2 dinucleotide splice site variants in the TP53 VCEP Specifications v2 (.xls).
DOI: 10.6084/m9.figshare.30423615
title: Additional file 2 of A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome

description: Additional file 2: Table S2. Bioinformatic predictions and corresponding PP3 and BP4 codes for every possible p53 missense variant using the TP53 specifications v2 (.xls).
DOI: 10.6084/m9.figshare.30423615.v1
title: Additional file 2 of A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome

description: Additional file 2: Table S2. Bioinformatic predictions and corresponding PP3 and BP4 codes for every possible p53 missense variant using the TP53 specifications v2 (.xls).
DOI: 10.6084/m9.figshare.30423618
title: Additional file 3 of A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome

description: Additional file 3: Table S3. Functional results for selected assays and corresponding preliminary PS3 and BS3 codes for every possible p53 missense variant using the TP53 specifications v2 (.xls).
DOI: 10.6084/m9.figshare.30423618.v1
title: Additional file 3 of A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome

description: Additional file 3: Table S3. Functional results for selected assays and corresponding preliminary PS3 and BS3 codes for every possible p53 missense variant using the TP53 specifications v2 (.xls).
DOI: 10.6084/m9.figshare.30423625
title: Additional file 1 of Interaction of potato-derived RG-I with galectin-3 and gene regulation in human mesenchymal stem cells

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.30423625.v1
title: Additional file 1 of Interaction of potato-derived RG-I with galectin-3 and gene regulation in human mesenchymal stem cells

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.30423636
title: Additional file 1 of Tracing exhumation and drainage dynamics in Taiwan's orogenic belt using detrital zircon U–Pb geochronology

description: Additional file 1.
DOI: 10.6084/m9.figshare.30423636.v1
title: Additional file 1 of Tracing exhumation and drainage dynamics in Taiwan's orogenic belt using detrital zircon U–Pb geochronology

description: Additional file 1.
DOI: 10.6084/m9.figshare.30423645
title: Additional file 1 of A-calibration: assessment of prediction models for survival data under censoring

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.30423645.v1
title: Additional file 1 of A-calibration: assessment of prediction models for survival data under censoring

description: Supplementary Material 1.
DOI: 10.15468/dl.r99m3z
title: Occurrence Download

description: A dataset containing 406907173 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Sclerocarpus spathulatus, Eriocaulon australe, Hyacinthella lazulina, Lonicera alpigena, Litsea australis, Mesembryanthemum guerichianum, Ononis leucotricha, Ononis tazaensis, Mesembryanthemum holense, Boronia chartacea, Boronia gracilipes, Boronia tetragona, Chaenostoma pauciflorum, Serjania palmeri, Fritillaria bithynica, Fritillaria hermonis, Fritillaria viridiflora, Fritillaria arsusiana, Ononis crinita, Viburnum orientale, Boronia barrettiorum, Capparis loranthifolia, Capparis tomentosa, Cyclamen alpinum, Cyclamen balearicum, Packera neomexicana, Mesembryanthemum resurgens, Mesembryanthemum viridiflorum, Ruellia jeddahica, Zieria robusta, Zieria aspalathoides, Correa bauerlenii, Taraxis grossa, Ononis oligophylla, Ononis megalostachys, Ononis talaverae, Anthocercis gracilis, Anthocercis sylvicola, Boronia denticulata, Halenia palmeri, Psephellus erivanensis, Psephellus erzincani, Psephellus vanensis, Boronia angustisepala, Capparis canescens, Lachnostachys coolgardiensis, Fritillaria ehrhartii, Ischaemum decumbens, Corydalis uniflora, Catasetum pendulum, Pistia stratiotes, Mesembryanthemum caudatum, Mesembryanthemum clandestinum, Pteris semiadnata, Plantae, Pterospora andromedea, Parnassia fimbriata, Correa calycina, Sclerocarpus sessilifolius, Backhousia sciadophora, Eriocaulon lividum, Lonicera iberica, Lonicera albiflora, Mesembryanthemum hypertrophicum, Mesembryanthemum schenckii, Boronia falcifolia, Boronia latipinna, Boronia rubiginosa, Fritillaria conica, Fritillaria elwesii, Fritillaria sororum, Ononis christii, Ononis cephalantha, Ruellia cordata, Ruellia corynotheca, Capparis cartilaginea, Corydalis budensis, Cyclamen graecum, Cyclamen repandum, Euchaetis elsieae, Euchaetis schlechteri, Mesembryanthemum pellitum, Hypocalymma, Fritillaria milasensis, Myrtus nivellei, Lonicera arborea, Ononis polyphylla, Ononis pusilla, Boronia coriacea, Boronia megastigma, Lasianthaea helianthoides, Fritillaria alburyana, Fritillaria graeca, Fritillaria uva-vulpis, Fritillaria viridea, Desfontainia fulgens, Ononis cristata, Capparis umbonata, Ononis natrix, Euchaetis glomerata)",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 406907173 records from 14825 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051542-251009101135966/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.28552430
title: Critical thinking data

description: This study develops a Critical Thinking-Real World Practice (CT-RWP) learning framework, integrating Challenge-Based Learning (CBL) and Values and Knowledge Education (VaKE) to enhance Critical Thinking skills (CTs). Traditional teaching models often fail to connect learning with real-world contexts, limiting their effectiveness in fostering CTs. CBL emphasizes practical challenges but lacks CT-focused instructional strategies, while VaKE promotes reflective decision-making but overlooks real-world applications. The CT-RWP framework combines the strengths of both models to address these gaps. Using a mixed-methods approach, nine experts evaluated the content and construct validity of the CT-RWP framework through interviews and questionnaires. Additionally, 111 first-year students from a university in eastern China were divided into an experimental group (n=51), which received the CT-RWP framework intervention, and a control group (n=60) following a traditional curriculum. CTs were assessed using a standardized CT scale. The results demonstrate strong alignment with key CT skills such as critical analysis, open-mindedness, and application. Meanwhile, the pilot study shows that the experimental group had significantly higher post-test CT scores compared to the control group, indicating the framework's practical effectiveness. These findings suggest the CT-RWP framework has significant potential for enhancing CT teaching practices.
DOI: 10.6084/m9.figshare.28552430.v1
title: 专家结构一致性数据1.sav

description: This study develops a Critical Thinking-Real World Practice (CT-RWP) learning framework, integrating Challenge-Based Learning (CBL) and Values and Knowledge Education (VaKE) to enhance Critical Thinking skills (CTs). Traditional teaching models often fail to connect learning with real-world contexts, limiting their effectiveness in fostering CTs. CBL emphasizes practical challenges but lacks CT-focused instructional strategies, while VaKE promotes reflective decision-making but overlooks real-world applications. The CT-RWP framework combines the strengths of both models to address these gaps. Using a mixed-methods approach, nine experts evaluated the content and construct validity of the CT-RWP framework through interviews and questionnaires. Additionally, 111 first-year students from a university in eastern China were divided into an experimental group (n=51), which received the CT-RWP framework intervention, and a control group (n=60) following a traditional curriculum. CTs were assessed using a standardized CT scale. The results demonstrate strong alignment with key CT skills such as critical analysis, open-mindedness, and application. Meanwhile, the pilot study shows that the experimental group had significantly higher post-test CT scores compared to the control group, indicating the framework's practical effectiveness. These findings suggest the CT-RWP framework has significant potential for enhancing CT teaching practices.
DOI: 10.5281/zenodo.14986387
title: CMIP6 input data usage information for IPCC WGI AR6 figure 3.35

description: The record contains information on input dataset usage and citation information from the WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) for the generation of figure 3.35 of the Sixth Assessment Report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC AR6 WGI). CMIP6 data that were used as input to this figure follow the Data Reference Syntax. Persistent Identifiers (PIDs) for data identification (provenance) are available for individual datasets as Handle IDs. DOIs for data citation are available on the following dataset collections: CMIP6 DOIs contain all datasets provided by an Earth System model to a CMIP6 experiment. The data subsets of CMIP6 dataset collections used in the IPCC AR6 WGI have DOIs at this granularity of a model contribution to an experiment. The AR6 subset DOIs are included because they reside in a long-term preservation archive hosted by the IPCC Data Distribution Centre (DDC).

The uploaded human-readable csv file provides a list of datasets/Handle IDs used for the generation of this figure grouped by the corresponding dataset collections they belong to. The machine-actionable json-ld file describes the record as Complex Citation Object (see Agarwal et al., 2024, https://doi.org/10.5281/zenodo.14106602) in a preliminary standard, using the following vocabulary to specify the different functions of the contained Linked Digital Objects: Credit (input dataset collection to be cited/to which credit is to be assigned), Provenance (dataset contributing information to the generation of the DataProduct), archivedAt (dataset collection with long-term preservation), DigitalDocument (referenced papers containing further information), DataProduct (generated final dataset), ImageObject (visualization of the DataProduct), SoftwareSourceCode (software applied to generate the DataProduct), Chapter (IPCC AR6 WGI chapter in which the DataProduct is used/referenced).

Use and cite this record when referring to the generation of IPCC WGI AR6 figure 3.35.
DOI: 10.5281/zenodo.14986388
title: CMIP6 input data usage information for IPCC WGI AR6 figure 3.35

description: The record contains information on input dataset usage and citation information from the WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) for the generation of figure 3.35 of the Sixth Assessment Report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC AR6 WGI). CMIP6 data that were used as input to this figure follow the Data Reference Syntax. Persistent Identifiers (PIDs) for data identification (provenance) are available for individual datasets as Handle IDs. DOIs for data citation are available on the following dataset collections: CMIP6 DOIs contain all datasets provided by an Earth System model to a CMIP6 experiment. The data subsets of CMIP6 dataset collections used in the IPCC AR6 WGI have DOIs at this granularity of a model contribution to an experiment. The AR6 subset DOIs are included because they reside in a long-term preservation archive hosted by the IPCC Data Distribution Centre (DDC).

The uploaded human-readable csv file provides a list of datasets/Handle IDs used for the generation of this figure grouped by the corresponding dataset collections they belong to. The machine-actionable json-ld file describes the record as Complex Citation Object (see Agarwal et al., 2024, https://doi.org/10.5281/zenodo.14106602) in a preliminary standard, using the following vocabulary to specify the different functions of the contained Linked Digital Objects: Credit (input dataset collection to be cited/to which credit is to be assigned), Provenance (dataset contributing information to the generation of the DataProduct), archivedAt (dataset collection with long-term preservation), DigitalDocument (referenced papers containing further information), DataProduct (generated final dataset), ImageObject (visualization of the DataProduct), SoftwareSourceCode (software applied to generate the DataProduct), Chapter (IPCC AR6 WGI chapter in which the DataProduct is used/referenced).

Use and cite this record when referring to the generation of IPCC WGI AR6 figure 3.35.
DOI: 10.5285/ef5ca18bcaf441d9993f181a058016ba
title: Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.35 (v20220614)

description: Data for Figure 3.35 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.35 shows Southern Annular Mode indices in the last millennium. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has two panels, and all the data are provided in sam_millennium.nc. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Annual SAM reconstructions. - Annual-mean SAM index by CMIP5 and CMIP6 Last Millennium simulations extended by historical simulations. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - sam_abram_runmean, sam_datwyler_runmean: thin blue and brown lines - sam_abram_lowpass, sam_datwyler_lowpass: thick blue and brown lines Panel b: - sam_cmip_runmean: thin lines . MIROC-ES2L: ensemble = 10 (violet) . MRI-ESM2-0: ensemble = 11 (green) . CMIP5: ensemble = 1, 2, 3, 4, 5, 6, 7, 8, 9 (grey) - sam_cmip_lowpass: thick lines . MIROC-ES2L: ensemble = 10 (violet) . MRI-ESM2-0: ensemble = 11 (green) . CMIP5: ensemble = 1, 2, 3, 4, 5, 6, 7, 8, 9 (grey) --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo - Link to the figure on the IPCC AR6 website
DOI: 10.5281/zenodo.14986391
title: CMIP6 input data usage information for IPCC WGI AR6 figure 3.37

description: The record contains information on input dataset usage and citation information from the WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) for the generation of figure 3.37 of the Sixth Assessment Report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC AR6 WGI). CMIP6 data that were used as input to this figure follow the Data Reference Syntax. Persistent Identifiers (PIDs) for data identification (provenance) are available for individual datasets as Handle IDs. DOIs for data citation are available on the following dataset collections: CMIP6 DOIs contain all datasets provided by an Earth System model to a CMIP6 experiment. The data subsets of CMIP6 dataset collections used in the IPCC AR6 WGI have DOIs at this granularity of a model contribution to an experiment. The AR6 subset DOIs are included because they reside in a long-term preservation archive hosted by the IPCC Data Distribution Centre (DDC).

The uploaded human-readable csv file provides a list of datasets/Handle IDs used for the generation of this figure grouped by the corresponding dataset collections they belong to. The machine-actionable json-ld file describes the record as Complex Citation Object (see Agarwal et al., 2024, https://doi.org/10.5281/zenodo.14106602) in a preliminary standard, using the following vocabulary to specify the different functions of the contained Linked Digital Objects: Credit (input dataset collection to be cited/to which credit is to be assigned), Provenance (dataset contributing information to the generation of the DataProduct), archivedAt (dataset collection with long-term preservation), DigitalDocument (referenced papers containing further information), DataProduct (generated final dataset), ImageObject (visualization of the DataProduct), SoftwareSourceCode (software applied to generate the DataProduct), Chapter (IPCC AR6 WGI chapter in which the DataProduct is used/referenced).

Use and cite this record when referring to the generation of IPCC WGI AR6 figure 3.37.
DOI: 10.5281/zenodo.14986392
title: CMIP6 input data usage information for IPCC WGI AR6 figure 3.37

description: The record contains information on input dataset usage and citation information from the WCRP Coupled Model Intercomparison Project Phase 6 (CMIP6) for the generation of figure 3.37 of the Sixth Assessment Report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC AR6 WGI). CMIP6 data that were used as input to this figure follow the Data Reference Syntax. Persistent Identifiers (PIDs) for data identification (provenance) are available for individual datasets as Handle IDs. DOIs for data citation are available on the following dataset collections: CMIP6 DOIs contain all datasets provided by an Earth System model to a CMIP6 experiment. The data subsets of CMIP6 dataset collections used in the IPCC AR6 WGI have DOIs at this granularity of a model contribution to an experiment. The AR6 subset DOIs are included because they reside in a long-term preservation archive hosted by the IPCC Data Distribution Centre (DDC).

The uploaded human-readable csv file provides a list of datasets/Handle IDs used for the generation of this figure grouped by the corresponding dataset collections they belong to. The machine-actionable json-ld file describes the record as Complex Citation Object (see Agarwal et al., 2024, https://doi.org/10.5281/zenodo.14106602) in a preliminary standard, using the following vocabulary to specify the different functions of the contained Linked Digital Objects: Credit (input dataset collection to be cited/to which credit is to be assigned), Provenance (dataset contributing information to the generation of the DataProduct), archivedAt (dataset collection with long-term preservation), DigitalDocument (referenced papers containing further information), DataProduct (generated final dataset), ImageObject (visualization of the DataProduct), SoftwareSourceCode (software applied to generate the DataProduct), Chapter (IPCC AR6 WGI chapter in which the DataProduct is used/referenced).

Use and cite this record when referring to the generation of IPCC WGI AR6 figure 3.37.
DOI: 10.6084/m9.figshare.28752215
title: Alignment_Fig2_Tilletia.fasta

description: concatenated ITS+LSU alignments underlying Fig. 2
DOI: 10.6084/m9.figshare.28752215.v1
title: Alignment_Fig2_Tilletia.fasta

description: concatenated ITS+LSU alignments underlying Fig. 2
DOI: 10.3535/f27-wcn-h1y
title: Cornus suecica L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.