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

description: A dataset containing 7510 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Coordinate reprojected, Geodetic datum assumed WGS84)",
 "OccurrenceStatus is Present",
 "TaxonKey is Dasylirion"
 ]
}

 The dataset includes 7510 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054200-250827131500795/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.30103171
title: Supplementary tables 1-11

description: <b>Supplementary Table 1.</b> The list of the closest 14 <i>Listeria monocytogenes</i> (Lm) homologs and the 11 reference Lm strains used for a phylogenetic analysis of the Lm strain AUF-2 and the Lm strain AUF-3 visualized in Figure 1.<b>Supplementary Table 2.</b> The novel allele profiles of virulence genes recognized for the <i>Listeria monocytogenes</i> (Lm) strain AUF-2 and the Lm strain AUF-3, and two reference Lm strains, either the Lm strain UKVDL4 or the Lm strain FSL-J1-158, respectively, versus the NCBI reference, the Lm strain EGD-e.<b>Supplementary</b><b> Table 3. </b>MLST characteristics the <i>Listeria monocytogenes</i> (Lm) strain AUF-2, the Lm strain AUF-3 and the Lm reference strains of different origin, whose whole genomes are available in the NCBI GenBank (https://www.ncbi.nlm.nih.gov/). The identical alleles are colored in red.<b>Supplementary</b><b> Table 4. </b>Comparison of the <i>L. monocytogenes</i> (Lm) strain AUF-2 genome versus the Lm strain AUF-3 genome and eight Lm reference genomes. Comparative analysis of the whole genomes of the Lm AUF-2 versus nine Lm strains were done on the BV-BRC platform (https://www.bv–brc.org/).<b>Supplementary</b><b> Table 5. </b>Comparison of either the <i>L. monocytogenes</i> (Lm) strain AUF-2 genome or the Lm strain AUF-3 genome with the NCBI reference sequence the Lm strain EGD-e. Comparative analysis of these Lm whole genomes was done on the BV-BRC platform (https://www.bv–brc.org/).<b>Supplementary Table 6.</b> Comparative differences between either the <i>L. monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 and other Lm reference strains of different origin. Comparison the number and allele profiles of genes/loci functionally annotated and associated with different Lm activity.<b>Supplementary Table 7. </b>The list of pseudogenes annotated in the <i>Listeria monocytogenes</i> (Lm) AUF-2 compare with the panel of reference Lm strains.<b>Supplementary Table 8.</b> The list of pseudogenes annotated in the <i>Listeria monocytogenes</i> (Lm) AUF-3 compare with the panel of reference Lm strains.<b>Supplementary Table 9.</b> Polymorphism of the T7SS genes annotated in either <i>Listeria monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 vs the Lm strain EGD-e, the NCBI Reference Sequence (NZ_CP023861.1).<b>Supplementary Table 10.</b> Comparative number of the genes capable to translate the proteins in the <i>Listeria monocytogenes</i> (Lm) strains AUF-2 and the Lm strain AUF-3 which were annotated as pseudogenes in the reference Lm strain EGD-e, the Lm strain FDAARGOS_607 and the Lm strain AUF.<b>Supplemental Table 11.</b> Comparative number of the genes identified in either the <i>Listeria monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 involved in the Lm in acidic resistance.
DOI: 10.6084/m9.figshare.30103171.v2
title: Complete genomes of <i>Listeria monocytogenes</i> AUF-2 and AUF-3, the vaccine strains against livestock listeriosis

description: <b>Supplementary Table 1.</b> The list of the closest 14 <i>Listeria monocytogenes</i> (Lm) homologs and the 11 reference Lm strains used for a phylogenetic analysis of the Lm strain AUF-2 and the Lm strain AUF-3 visualized in Figure 1.<b>Supplementary Table 2.</b> The novel allele profiles of virulence genes recognized for the <i>Listeria monocytogenes</i> (Lm) strain AUF-2 and the Lm strain AUF-3, and two reference Lm strains, either the Lm strain UKVDL4 or the Lm strain FSL-J1-158, respectively, versus the NCBI reference, the Lm strain EGD-e.<b>Supplementary</b><b> Table 3. </b>MLST characteristics the <i>Listeria monocytogenes</i> (Lm) strain AUF-2, the Lm strain AUF-3 and the Lm reference strains of different origin, whose whole genomes are available in the NCBI GenBank (https://www.ncbi.nlm.nih.gov/). The identical alleles are colored in red.<b>Supplementary</b><b> Table 4. </b>Comparison of the <i>L. monocytogenes</i> (Lm) strain AUF-2 genome versus the Lm strain AUF-3 genome and eight Lm reference genomes. Comparative analysis of the whole genomes of the Lm AUF-2 versus nine Lm strains were done on the BV-BRC platform (https://www.bv–brc.org/).<b>Supplementary</b><b> Table 5. </b>Comparison of either the <i>L. monocytogenes</i> (Lm) strain AUF-2 genome or the Lm strain AUF-3 genome with the NCBI reference sequence the Lm strain EGD-e. Comparative analysis of these Lm whole genomes was done on the BV-BRC platform (https://www.bv–brc.org/).<b>Supplementary Table 6.</b> Comparative differences between either the <i>L. monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 and other Lm reference strains of different origin. Comparison the number and allele profiles of genes/loci functionally annotated and associated with different Lm activity.<b>Supplementary Table 7. </b>The list of pseudogenes annotated in the <i>Listeria monocytogenes</i> (Lm) AUF-2 compare with the panel of reference Lm strains.<b>Supplementary Table 8.</b> The list of pseudogenes annotated in the <i>Listeria monocytogenes</i> (Lm) AUF-3 compare with the panel of reference Lm strains.<b>Supplementary Table 9.</b> Polymorphism of the T7SS genes annotated in either <i>Listeria monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 vs the Lm strain EGD-e, the NCBI Reference Sequence (NZ_CP023861.1).<b>Supplementary Table 10.</b> Comparative number of the genes capable to translate the proteins in the <i>Listeria monocytogenes</i> (Lm) strains AUF-2 and the Lm strain AUF-3 which were annotated as pseudogenes in the reference Lm strain EGD-e, the Lm strain FDAARGOS_607 and the Lm strain AUF.<b>Supplemental Table 11.</b> Comparative number of the genes identified in either the <i>Listeria monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 involved in the Lm in acidic resistance.
DOI: 10.6084/m9.figshare.30103171.v3
title: Supplementary tables 1-11

description: <b>Supplementary Table 1.</b> The list of the closest 14 <i>Listeria monocytogenes</i> (Lm) homologs and the 11 reference Lm strains used for a phylogenetic analysis of the Lm strain AUF-2 and the Lm strain AUF-3 visualized in Figure 1.<b>Supplementary Table 2.</b> The novel allele profiles of virulence genes recognized for the <i>Listeria monocytogenes</i> (Lm) strain AUF-2 and the Lm strain AUF-3, and two reference Lm strains, either the Lm strain UKVDL4 or the Lm strain FSL-J1-158, respectively, versus the NCBI reference, the Lm strain EGD-e.<b>Supplementary</b><b> Table 3. </b>MLST characteristics the <i>Listeria monocytogenes</i> (Lm) strain AUF-2, the Lm strain AUF-3 and the Lm reference strains of different origin, whose whole genomes are available in the NCBI GenBank (https://www.ncbi.nlm.nih.gov/). The identical alleles are colored in red.<b>Supplementary</b><b> Table 4. </b>Comparison of the <i>L. monocytogenes</i> (Lm) strain AUF-2 genome versus the Lm strain AUF-3 genome and eight Lm reference genomes. Comparative analysis of the whole genomes of the Lm AUF-2 versus nine Lm strains were done on the BV-BRC platform (https://www.bv–brc.org/).<b>Supplementary</b><b> Table 5. </b>Comparison of either the <i>L. monocytogenes</i> (Lm) strain AUF-2 genome or the Lm strain AUF-3 genome with the NCBI reference sequence the Lm strain EGD-e. Comparative analysis of these Lm whole genomes was done on the BV-BRC platform (https://www.bv–brc.org/).<b>Supplementary Table 6.</b> Comparative differences between either the <i>L. monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 and other Lm reference strains of different origin. Comparison the number and allele profiles of genes/loci functionally annotated and associated with different Lm activity.<b>Supplementary Table 7. </b>The list of pseudogenes annotated in the <i>Listeria monocytogenes</i> (Lm) AUF-2 compare with the panel of reference Lm strains.<b>Supplementary Table 8.</b> The list of pseudogenes annotated in the <i>Listeria monocytogenes</i> (Lm) AUF-3 compare with the panel of reference Lm strains.<b>Supplementary Table 9.</b> Polymorphism of the T7SS genes annotated in either <i>Listeria monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 vs the Lm strain EGD-e, the NCBI Reference Sequence (NZ_CP023861.1).<b>Supplementary Table 10.</b> Comparative number of the genes capable to translate the proteins in the <i>Listeria monocytogenes</i> (Lm) strains AUF-2 and the Lm strain AUF-3 which were annotated as pseudogenes in the reference Lm strain EGD-e, the Lm strain FDAARGOS_607 and the Lm strain AUF.<b>Supplemental Table 11.</b> Comparative number of the genes identified in either the <i>Listeria monocytogenes</i> (Lm) strain AUF-2 or the Lm strain AUF-3 involved in the Lm in acidic resistance.
DOI: 10.6084/m9.figshare.27221136
title: Data and Code for: <i>Moving towards more holistic machine learning-based approaches for classification problems in animal studies</i>

description: Machine-learning (ML) is revolutionizing field and laboratory studies of animals. However, a challenge when deploying ML for classification tasks is ensuring the models are reliable. Currently, we evaluate models using performance metrics alone (e.g., precision, recall, F1), but these can overlook the ultimate aim, which is not the outputs themselves (e.g. detected species or individual identities, or behaviour) but their incorporation for hypothesis testing. As improving performance metrics has diminishing returns, particularly when data are inherently noisy (as human-labelled, animal-based data often are), researchers are faced with the conundrum of investing more time in maximising metrics versus answering biological questions. This raises the question: how much noise can we accept in ML models? Here, we start by describing an under-reported factor that can cause metrics to underestimate model performance. Specifically, ambiguity between categories or mistakes in labelling test data produces hard ceilings that limit performance metrics. This likely widespread issue means that many models could be performing better than their metrics suggest. Next, we argue and show that imperfect models (e.g. low F1 scores) can still be useable. Using a case study on ML-identified behaviour from vulturine guineafowl accelerometer data, we first propose a simulation framework to evaluate robustness of hypothesis testing using models that make classification errors. Second, we show how to determine the utility of a model by supplementing existing performance metrics with ‘biological validations’. This involves applying ML models to unlabelled data and using the models’ outputs to test hypotheses for which we can anticipate the outcome. Together, we show that effects sizes and expected biological patterns can be detected even when performance metrics are relatively low (e.g., F1: 60-70%). In doing so, we provide a roadmap for validation approaches of ML classification models tailored to research in animal behaviour, and other fields with noisy, biological data.
DOI: 10.6084/m9.figshare.27221136.v1
title: Data and Code for: <i>Moving towards more holistic machine learning-based approaches for classification problems in animal studies</i>

description: Machine-learning (ML) is revolutionizing field and laboratory studies of animals. However, a challenge when deploying ML for classification tasks is ensuring the models are reliable. Currently, we evaluate models using performance metrics alone (e.g., precision, recall, F1), but these can overlook the ultimate aim, which is not the outputs themselves (e.g. detected species or individual identities, or behaviour) but their incorporation for hypothesis testing. As improving performance metrics has diminishing returns, particularly when data are inherently noisy (as human-labelled, animal-based data often are), researchers are faced with the conundrum of investing more time in maximising metrics versus answering biological questions. This raises the question: how much noise can we accept in ML models? Here, we start by describing an under-reported factor that can cause metrics to underestimate model performance. Specifically, ambiguity between categories or mistakes in labelling test data produces hard ceilings that limit performance metrics. This likely widespread issue means that many models could be performing better than their metrics suggest. Next, we argue and show that imperfect models (e.g. low F1 scores) can still be useable. Using a case study on ML-identified behaviour from vulturine guineafowl accelerometer data, we first propose a simulation framework to evaluate robustness of hypothesis testing using models that make classification errors. Second, we show how to determine the utility of a model by supplementing existing performance metrics with ‘biological validations’. This involves applying ML models to unlabelled data and using the models’ outputs to test hypotheses for which we can anticipate the outcome. Together, we show that effects sizes and expected biological patterns can be detected even when performance metrics are relatively low (e.g., F1: 60-70%). In doing so, we provide a roadmap for validation approaches of ML classification models tailored to research in animal behaviour, and other fields with noisy, biological data.
DOI: 10.15468/dl.psmntt
title: Occurrence Download

description: A dataset containing 4304410 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Material sample, Machine Observation)",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Geodetic datum assumed WGS84, Coordinate reprojected)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4304410 records from 514 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054165-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2lwnkq
title: CCDC 2409864: Experimental Crystal Structure Determination

description: Related Article: Xinlei Huangfu, Wei Liu, Zhiyi Song, Junnian Wei, Wen-Xiong Zhang|2025|Chem (Cell Press)|11|102496|doi:10.1016/j.chempr.2025.102496
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2mbvzt
title: CCDC 2423517: Experimental Crystal Structure Determination

description: Related Article: Xinlei Huangfu, Wei Liu, Zhiyi Song, Junnian Wei, Wen-Xiong Zhang|2025|Chem (Cell Press)|11|102496|doi:10.1016/j.chempr.2025.102496
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.wzkume
title: Occurrence Download

description: A dataset containing 312 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Cariama cristata"
 ]
}

 The dataset includes 312 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054206-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f29htg
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Guatemala",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhizophora mangle"
 ]
}

 The dataset includes 60 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054205-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13032897
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.84wqa3
title: Occurrence Download

description: A dataset containing 70143 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Alopecurus aequalis"
 ]
}

 The dataset includes 70143 records from 1007 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054145-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ujal0l
title: Occurrence Download

description: A dataset containing 34663 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix viminalis L.",
 "HasCoordinate is true",
 {
 "or" : [
 "BasisOfRecord is Fossil",
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Machine Observation",
 "BasisOfRecord is Observation",
 "BasisOfRecord is Literature Occurrence",
 "BasisOfRecord is Unknown evidence"
 ]
 }
 ]
}

 The dataset includes 34663 records from 168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038977-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2021-04.2215807/2359214
title: Data for EMSL Project 49510 from April 2021
DOI: 10.25549/examiner-c44-28604
title: Christmas Parade ...Van Nuys, 1951

description: 7 images. Christmas Parade...Van Nuys, 7 December 1951. Picture of Religious Floats from several churches and shots of crowds and spectators.; Caption slip reads: "Photographer: Glickman. Date: 1951-12-07. Reporter: Glickman. Assignment; Van Nuys Xmas Parade. G21: The Annunciation float by St. Elizabeth's Catholic church of Van Nuys. G22: First presbyterian Church of Van Nuys, Journey to the Inn. G18: Sherwood Community church... No Room at the Inn. G31: Central Christian Church of Van Nuys ... Bringing gifts to the Christ Child. G32: Emanuel Lutheran Church of No. Hol. Christ inviting Peter to become a fisher of men. Crowd shots ... 'Here comes the parade'". Edits: "G17: Four Square Gospel Church of Los Angeles... Shepherds in the Night".
DOI: 10.15468/dl.6rdrqh
title: Occurrence Download

description: A dataset containing 1290 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bombycilla garrulus (Linnaeus, 1758)",
 "DatasetKey is Observation.org, Nature data from around the World",
 "Country is one of (Germany, France, Spain, Portugal, Denmark, Austria, Italy, Switzerland, Greece, Poland, Hungary, Slovenia, Sweden, Norway, Slovakia, Montenegro, Croatia, North Macedonia, Serbia, Iceland, Ireland, United Kingdom of Great Britain and Northern Ireland, Albania, Bosnia and Herzegovina, Bulgaria, Finland)"
 ]
}

 The dataset includes 1290 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006714-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xp5jnk
title: Occurrence Download

description: A dataset containing 34932 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cymbilaimus lineatus (Leach, 1814)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 34932 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030838-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/examiner-c44-28401
title: Shooting at Cafe (North Hollywood) 7456 Laurel Canyon Boulevard, 1951

description: 6 images. Shooting at Cafe (North Hollywood) 7456 Laurel Canyon Boulevard, 6 December 1951. Detective Dan Shea; Thomas Colclough (victim), bartender; Hilda Colclough (wife); Willis P. Scott (victim); Angeline Fones (Nurse).
DOI: 10.25582/data.2021-04.2215746/2359215
title: Data for EMSL Project 49510 from April 2021
DOI: 10.15468/dl.w49oop
title: Occurrence Download

description: A dataset containing 13477 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix lapponum L.",
 "HasCoordinate is true",
 {
 "or" : [
 "BasisOfRecord is Fossil",
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Machine Observation",
 "BasisOfRecord is Observation",
 "BasisOfRecord is Literature Occurrence",
 "BasisOfRecord is Unknown evidence"
 ]
 }
 ]
}

 The dataset includes 13477 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038981-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gc4s6h
title: Occurrence Download

description: A dataset containing 12122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunella modularis (Linnaeus, 1758)",
 "DatasetKey is Observation.org, Nature data from around the World",
 "Country is one of (Germany, France, Spain, Portugal, Denmark, Austria, Italy, Switzerland, Greece, Poland, Hungary, Slovenia, Sweden, Norway, Slovakia, Montenegro, Croatia, North Macedonia, Serbia, Iceland, Ireland, United Kingdom of Great Britain and Northern Ireland, Albania, Bosnia and Herzegovina, Bulgaria, Finland)"
 ]
}

 The dataset includes 12122 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006718-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/examiner-c44-26390
title: Drivers license returned, 1951

description: 5 images. Drivers license returned, 26 November 1951. Michael Thomas O'Rourke -- 22 years; Joan Adams -- 19 years; Judge A. J. Bernhardt.
DOI: 10.25582/data.2021-04.2216435/2359216
title: Data for EMSL Project 49510 from April 2021
DOI: 10.15468/dl.d28zje
title: Occurrence Download

description: A dataset containing 7110 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Phytolacca dioica L., Phytolacca dioica var. ovatifolia Chodat, Pircunia dioica (L.) Moq., Sarcoca dioica (L.) Raf.)"
 ]
}

 The dataset includes 7110 records from 268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030836-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.88tjma
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amphalius clarus kunlunensis Yu & Wang, 1981",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008663-231120084113126/datasets/export for details.