cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31055569.v1
title: Supplementary Material for: Assessment of Generative Artificial Intelligence Policies Across Dermatology Journals

description: Introduction: The rapid integration of generative artificial intelligence (GenAI) into academic research has prompted ethical and regulatory concerns, particularly regarding its responsible use in scholarly publishing. Despite emerging recommendations from international organizations such as the Committee on Publication Ethics (COPE) and the International Committee of Medical Journal Editors (ICMJE), journal-specific guidance remains inconsistent. 
Methods: This study evaluated the presence and characteristics of GenAI-related policies across 92 dermatology journals indexed in the 2024 Journal Citation Reports. Four reviewers independently assessed author instructions and publisher policies, collecting journal metrics and applying logistic regression to explore associations with guideline adoption. 
Results: GenAI-specific guidance was found in 82.6% of journals, with 60.5% linking to publisher-level policies. Most journals (90.8%) prohibited GenAI authorship and required author accountability, yet only 2.6% referenced ICMJE guidance. Disclosure of GenAI use was mandated by 98.7%, although only a minority required specification of tool version (28.0%) or manufacturer (17.3%). GenAI image generation was addressed in 55.3% of policies, with ChatGPT mentioned by 46.1% of journals. COPE membership and use of COPE AI guidance were significantly associated with the presence of journal-level GenAI policies. While journals with GenAI guidance exhibited higher impact and citation metrics in univariable analysis, no predictors remained significant in multivariable models. 
Conclusion: These findings highlight broad yet uneven adoption of GenAI policies in dermatology publishing. Gaps in specificity, transparency, and alignment with international standards may pose risks to research integrity, emphasizing the need for clearer, standardized, and field-specific editorial guidance on GenAI use.
DOI: 10.15156/bio/sh1383339.10fu
title: SH1383339.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1383340.10fu
title: SH1383340.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1383347.10fu
title: SH1383347.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1383348.10fu
title: SH1383348.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1383350.10fu
title: SH1383350.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1383351.10fu
title: SH1383351.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1383353.10fu
title: SH1383353.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.57745/qa3jhc
title: GCA_001606085.1.k21.kmc_suf

description: :unav
DOI: 10.57745/cafql6
title: GCA_963854185.1.k21.kmc_suf

description: :unav
DOI: 10.57745/hkugts
title: NC_005805.k21.kmc_pre

description: :unav
DOI: 10.57745/6buodq
title: NC_012928.k21.kmc_pre

description: :unav
DOI: 10.57745/96hxca
title: GCF_902655055-1.k21.kmc_suf

description: :unav
DOI: 10.57745/dyvage
title: GCA_003317085.1.k21.kmc_suf

description: :unav
DOI: 10.57745/iitzbb
title: NC_001606.k21.kmc_pre

description: :unav
DOI: 10.57745/2jgsbi
title: NC_052758.1.k21.kmc_pre

description: :unav
DOI: 10.57745/z5edzw
title: Kmers library for identifying endemic diadromous fish in Europe from degraded DNA (e.g., ancient DNA) - Use of this data with the DeFIS pipeline (Detection of Fauna and Flora: Identification of Species)

description: This dataset provides a curated k-mer library (k = 21) built from reference genomes of European endemic diadromous fishes, complemented with outgroup genomes (e.g., human and other non-target species) to help detect and interpret potential contamination in ancient or low-quality DNA samples. The library was generated with KMC (stored as .kmc_pre/.kmc_suf files) and is intended for use with the DeFiS pipeline (Detection of Fauna and flora: Identification of Species), which identifies the most likely species by comparing k-mer dictionaries between reference genomes and sequencing samples, using metrics such as k-mer ratios and Jaccard similarity. These precomputed reference k-mer sets are designed to speed up analyses and reduce computational cost by allowing repeated comparisons of a sample against multiple candidate reference genomes. The associated metadata table documents the taxonomic coverage, genome sources (GenBank/NCBI accessions), and reference links used to build the library. Information on how these data were generated and how to use them is also available here: https://bios4biol.pages-forge.inrae.fr/DeFiS/
DOI: 10.15468/dl.jyn6k4
title: Occurrence Download

description: A dataset containing 960 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Abutilon pannosum (G.Forst.) Schltdl."
 ]
}

 The dataset includes 960 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0292664-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2rghqb
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Dicaeum nitidum",
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Year 2011-2021",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069802-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.28jwww
title: Occurrence Download

description: A dataset containing 22673 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunus persica (L.) Stokes",
 "Year is greater than or equal to 1981",
 "HasCoordinate is true"
 ]
}

 The dataset includes 22673 records from 371 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0302466-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nwmdj9
title: Occurrence Download

description: A dataset containing 3865 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pterocarpus officinalis Jacq."
 ]
}

 The dataset includes 3865 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004830-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3nhzzd
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oxalis adenodes Sond."
 ]
}

 The dataset includes 42 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055923-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.syak2n
title: Occurrence Download

description: A dataset containing 613 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ectopistes migratorius (Linnaeus, 1766))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 613 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0292665-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hcx48g
title: Occurrence Download

description: A dataset containing 86627 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acer rubrum L.",
 "Year is greater than or equal to 1981",
 "HasCoordinate is true"
 ]
}

 The dataset includes 86627 records from 178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0300554-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qaqayy
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhus potaninii Maxim.",
 "Year is greater than or equal to 1981",
 "HasCoordinate is true"
 ]
}

 The dataset includes 10 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0302478-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rvd2df
title: Occurrence Download

description: A dataset containing 25038 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Oncorhynchus clarkii (Richardson, 1836))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 25038 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067637-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qzveej
title: Occurrence Download

description: A dataset containing 6762 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Austrostipa rudis (Spreng.) S.W.L.Jacobs & J.Everett"
 ]
}

 The dataset includes 6762 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0145135-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w5tqzs
title: Occurrence Download

description: A dataset listing the 121724 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence, Machine Observation, Material sample, Specimen)"
 ]
}

 The dataset's 121724 records were derived from 2340 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0302459-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57907/mirri/xugxfy
title: MIRRI0097350

description: Organism type: Bacteria ; Taxon name: Stenotrophomonas maltophilia ; Collection: NCCB 94078
DOI: 10.3535/are-jpl-3y6
title: Achnanthes brevipes var. capensis (Kütz.) Grunow

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/xs6-n6n-pz4
title: Calvatia cyathiformis (Bosc) Morgan

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.57907/mirri/547jqm
title: MIRRI0098306

description: Organism type: Bacteria ; Taxon name: Brevibacillus laterosporus ; Collection: NCCB 100740
DOI: 10.57907/mirri/9d9yce/qj9qzj
title: MIRRI0098730.json

description: Strain json file
DOI: 10.57907/mirri/athbfi
title: MIRRI0098946

description: Organism type: Algae ; Taxon name: Seminavis robusta ; Collection: DCG 0551 ; Country: Netherlands
DOI: 10.57907/mirri/dis6dy/4qvmng
title: MIRRI0098904.json

description: Strain json file
DOI: 10.57907/mirri/ieeyrt/nzuvf0
title: MIRRI0098843.json

description: Strain json file
DOI: 10.57907/mirri/in1mtk
title: MIRRI0098673

description: Organism type: Algae ; Taxon name: Sellaphora capitata ; Collection: DCG 0166 ; Country: Belgium
DOI: 10.57907/mirri/oeynrn/rk09eb
title: MIRRI0098884.json

description: Strain json file
DOI: 10.57907/mirri/qahsoj
title: MIRRI0098912

description: Organism type: Algae ; Taxon name: Seminavis robusta ; Collection: DCG 0514 ; Country: Netherlands
DOI: 10.57907/mirri/sn0dla
title: MIRRI0098929

description: Organism type: Algae ; Taxon name: Humidophila gallica ; Collection: DCG 0534 ; Country: Germany
DOI: 10.57907/mirri/wrptjv/haakno
title: MIRRI0098919.json

description: Strain json file
DOI: 10.3535/2tg-9aa-agc
title: Jungermannia L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/5q6-y6y-3vb
title: Stipa pennata L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.57907/mirri/03t6ov
title: MIRRI0098259

description: Organism type: Bacteria ; Taxon name: Legionella pneumophila subsp. pneumophila ; Collection: NCCB 100647
DOI: 10.57907/mirri/7wthri
title: MIRRI0097437

description: Organism type: Bacteria ; Taxon name: Halococcus morrhuae ; Collection: NCCB 85051
DOI: 10.57907/mirri/90gnmt/q5ifh6
title: MIRRI0098312.json

description: Strain json file
DOI: 10.57907/mirri/bhttpd
title: MIRRI0097428

description: Organism type: Bacteria ; Taxon name: Sulfobacillus thermosulfidooxidans ; Collection: NCCB 85012
DOI: 10.57907/mirri/bjgs21/9qgzkj
title: MIRRI0098175.json

description: Strain json file
DOI: 10.57907/mirri/c4a4dj
title: MIRRI0098266

description: Organism type: Bacteria ; Taxon name: Klebsiella variicola ; Collection: NCCB 100656 ; Country: Mexico
DOI: 10.57907/mirri/ddi5kr
title: MIRRI0097401

description: Organism type: Bacteria ; Taxon name: Acinetobacter ; Collection: NCCB 82050
DOI: 10.57907/mirri/dj3llm
title: MIRRI0097426

description: Organism type: Bacteria ; Taxon name: Hyphomicrobium denitrificans ; Collection: NCCB 84101
DOI: 10.57907/mirri/dj3llm/hsambk
title: MIRRI0097426.json

description: Strain json file
DOI: 10.57907/mirri/el0ci9
title: MIRRI0098235

description: Organism type: Bacteria ; Taxon name: Campylobacter coli ; Collection: NCCB 100621 ; Country: Belgium
DOI: 10.57907/mirri/fipsum/ys9bno
title: MIRRI0097407.json

description: Strain json file
DOI: 10.57907/mirri/jlneln
title: MIRRI0097403

description: Organism type: Bacteria ; Taxon name: Acinetobacter calcoaceticus ; Collection: NCCB 82056
DOI: 10.57907/mirri/k16mv0
title: MIRRI0098224

description: Organism type: Bacteria ; Taxon name: Geobacillus stearothermophilus ; Collection: NCCB 100604
DOI: 10.57907/mirri/kh8lzy
title: MIRRI0097418

description: Organism type: Bacteria ; Taxon name: Cupriavidus necator ; Collection: NCCB 84050
DOI: 10.57907/mirri/kw8ffd
title: MIRRI0097434

description: Organism type: Bacteria ; Taxon name: Acinetobacter pittii ; Collection: NCCB 85032
DOI: 10.57907/mirri/muhluo
title: MIRRI0097389

description: Organism type: Bacteria ; Taxon name: Moraxella (branhamella) sp. ; Collection: NCCB 82022
DOI: 10.57907/mirri/nj5ash/8qu02a
title: MIRRI0098216.json

description: Strain json file
DOI: 10.57907/mirri/obxqkx/rwnj5z
title: MIRRI0098205.json

description: Strain json file
DOI: 10.57907/mirri/pdew0m/r2iuug
title: MIRRI0098227.json

description: Strain json file
DOI: 10.57907/mirri/pkhmfo
title: MIRRI0098215

description: Organism type: Bacteria ; Taxon name: Streptomyces muensis ; Collection: NCCB 100592 ; Country: Singapore
DOI: 10.57907/mirri/rv6hdg
title: MIRRI0098184

description: Organism type: Bacteria ; Taxon name: Pseudomonas ; Collection: NCCB 100551 ; Country: Netherlands
DOI: 10.57907/mirri/stchtx/u2zv3k
title: MIRRI0097410.json

description: Strain json file
DOI: 10.57907/mirri/taovkj/oam6l3
title: MIRRI0098251.json

description: Strain json file
DOI: 10.57907/mirri/w56pvz
title: MIRRI0098246

description: Organism type: Bacteria ; Taxon name: Corynebacterium lubricantis ; Collection: NCCB 100633
DOI: 10.57907/mirri/xc4kim
title: MIRRI0098195

description: Organism type: Bacteria ; Taxon name: Brachybacterium ; Collection: NCCB 100564 ; Country: Turkey
DOI: 10.57907/mirri/ygpaz0
title: MIRRI0097279

description: Organism type: Bacteria ; Taxon name: Propionibacterium ; Collection: NCCB 79035
DOI: 10.3535/83h-c1v-er4
title: Hypnum Hedw.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8ms-tc2-pcr
title: Usnea

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.57907/mirri/75kdjg/pf6cke
title: MIRRI0097260.json

description: Strain json file
DOI: 10.57907/mirri/7u2man
title: MIRRI0097257

description: Organism type: Bacteria ; Taxon name: Acetobacter ghanensis ; Collection: NCCB 100328 ; Country: Ethiopia
DOI: 10.57907/mirri/9vht5o/ut1fkj
title: MIRRI0097334.json

description: Strain json file
DOI: 10.57907/mirri/fk23fs
title: MIRRI0098316

description: Organism type: Bacteria ; Taxon name: Acinetobacter baumannii ; Collection: NCCB 100750 ; Country: Spain