cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31046215
title: Data and code

description: This study primarily focuses on the global-scale assessment of the effects of organic amendments, inorganicamendments, and organic + inorganic amendments on global saline-alkali soil remediation, soil organic carbonsequestration, and plant productivity improvement, We evaluated which environmental factors are the main drivers of different amendments and extended this to global patterns
DOI: 10.6084/m9.figshare.31046215.v1
title: Data and code

description: This study primarily focuses on the global-scale assessment of the effects of organic amendments, inorganicamendments, and organic + inorganic amendments on global saline-alkali soil remediation, soil organic carbonsequestration, and plant productivity improvement, We evaluated which environmental factors are the main drivers of different amendments and extended this to global patterns
DOI: 10.15468/dl.x3qpv9
title: Occurrence Download

description: A dataset containing 16746 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((63.41614 39.551,64.84401 39.551,64.84401 40.34136,63.41614 40.34136,63.41614 39.551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 16746 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003371-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18217913
title: Dataset for "Climate Drivers of Ocean Productivity and Oxygenation Across the Phanerozoic"

description: All figure data can be extracted by loading the data files into MATLAB. For each figure panel, the original data are stored in allFigData{num}.Axes{1}.Objects{1}, where "num" corresponds to the panel index. Additional axis information can be found in allFigData{num}.Axes{1}.
DOI: 10.5281/zenodo.18217914
title: Dataset for "Climate Drivers of Ocean Productivity and Oxygenation Across the Phanerozoic"

description: All figure data can be extracted by loading the data files into MATLAB. For each figure panel, the original data are stored in allFigData{num}.Axes{1}.Objects{1}, where "num" corresponds to the panel index. Additional axis information can be found in allFigData{num}.Axes{1}.
DOI: 10.15468/dl.vhn3b2
title: Occurrence Download

description: A dataset listing the 9 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Continent is Asia",
 "Country is one of (Chinese Taipei, China)",
 "OccurrenceStatus is Present",
 "TaxonKey is Biddulphiales"
 ]
}

 The dataset's 9 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003369-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q7qkkc
title: Occurrence Download

description: A dataset containing 14164442 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is China"
 ]
}

 The dataset includes 14164442 records from 7557 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003356-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v9eqxa
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Seligeria oelandica",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 52 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023754-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tgnehw
title: Occurrence Download

description: A dataset containing 198 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bauhinia glauca tenuiflora"
 ]
}

 The dataset includes 198 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010211-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wkwsb7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carassius auratus",
 "Country is Moldova, Republic of",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010212-250711103210423/datasets/export for details.
DOI: 10.15468/dl.rxufem
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carassius auratus",
 "Country is Morocco",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010213-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k2h93e
title: Occurrence Download

description: A dataset containing 332 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hyptis ditassoides"
 ]
}

 The dataset includes 332 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010214-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.az2q8x
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tecoma stans",
 "Country is Cabo Verde",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010215-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/7d54s5
title: Occurrence dataset of bats (Mammalia, Chiroptera) from Xuan Nha Nature Reserve, Son La Province, northwestern Vietnam

description: This dataset presents species occurrence records of bats collected from Xuan Nha Nature Reserve, Van Ho District, Son La Province, northwestern Vietnam. Field surveys were conducted in August 2024 as part of the Nagao Natural Environment Foundation's biodiversity research program. For every occurrence record, information on location (GPS coordinates), date, sex, reproductive condition, and trap type is provided.
DOI: 10.15468/dl.zawtxr
title: Occurrence Download

description: A dataset containing 7296329 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Tachycineta bicolor)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 7296329 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010180-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zk8t2c
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudorasbora parva",
 "Country is Lao People’s Democratic Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010216-250711103210423/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.29552543
title: ORDerly Transformer Models for chemical tasks

description: Transformer models trained on tasks in organic chemistry on ORDerly benchmark datasets.ORDerly_retro: Retrosynthesis prediction (prediction reactants given a desired product)ORDerly_forward_separated: Forward reaction prediction (predict reaction products given reactants, solvents, and agents), with reactants separated by &gt; from the solvents and agents in the reaction string.ORDerly_forward_mixed: Forward reaction prediction (predict reaction products given reactants, solvents, and agents), with reactants, solvents and agents mixed together in the reaction string.non-uspto-eval: Evaluation of transformer models trained on USPTO data on non-uspto data available in the Open Reaction Database.Full details can be found in our paper: https://chemrxiv.org/engage/chemrxiv/article-details/64ca5d3e4a3f7d0c0d78ca42Neurips workshop paper: https://openreview.net/forum?id=R8FQMsECISCode: https://github.com/sustainable-processes/orderlyThe supplementary datasets used for this work can be found here: https://doi.org/10.6084/m9.figshare.23502372.v3Transformer model architecture is from Molecular Transformer: https://pubs.acs.org/doi/10.1021/acscentsci.9b00576Find the results, models, and checkpoints within MolecularTransformer/experiments. Note that the "wandb" folder was deleted since figshare only allows uploads up to 500 files.Notes:There's a limit of 500 files in figshare, so I deleted the the "docs" and "onmt", and "OpenNMT_py.egg-info" , and "tools" folders from all folders except "ORDerly_retro". I also deleted all wandb-associated files and all checkpoint files.Empty files cannot be uploaded to figshare, so you have to create these yourself, where appropriate (e.g. MolecularTransformer/onmt/tests/__init__.py and non-uspto-eval/MolecularTransformer/experiments/models/ofs_1.pt).Feel free to email me, Daniel Wigh, at dsw46@cam.ac.uk or daniel@reactwise.com or my supervisor Alexei A. Lapkin.
DOI: 10.6084/m9.figshare.29552543.v4
title: ORDerly Transformer Models for chemical tasks

description: Transformer models trained on tasks in organic chemistry on ORDerly benchmark datasets.ORDerly_retro: Retrosynthesis prediction (prediction reactants given a desired product)ORDerly_forward_separated: Forward reaction prediction (predict reaction products given reactants, solvents, and agents), with reactants separated by &gt; from the solvents and agents in the reaction string.ORDerly_forward_mixed: Forward reaction prediction (predict reaction products given reactants, solvents, and agents), with reactants, solvents and agents mixed together in the reaction string.non-uspto-eval: Evaluation of transformer models trained on USPTO data on non-uspto data available in the Open Reaction Database.Full details can be found in our paper: https://chemrxiv.org/engage/chemrxiv/article-details/64ca5d3e4a3f7d0c0d78ca42Neurips workshop paper: https://openreview.net/forum?id=R8FQMsECISCode: https://github.com/sustainable-processes/orderlyThe supplementary datasets used for this work can be found here: https://doi.org/10.6084/m9.figshare.23502372.v3Transformer model architecture is from Molecular Transformer: https://pubs.acs.org/doi/10.1021/acscentsci.9b00576Find the results, models, and checkpoints within MolecularTransformer/experiments. Note that the "wandb" folder was deleted since figshare only allows uploads up to 500 files.Notes:There's a limit of 500 files in figshare, so I deleted the the "docs" and "onmt", and "OpenNMT_py.egg-info" , and "tools" folders from all folders except "ORDerly_retro". I also deleted all wandb-associated files and all checkpoint files.Empty files cannot be uploaded to figshare, so you have to create these yourself, where appropriate (e.g. MolecularTransformer/onmt/tests/__init__.py and non-uspto-eval/MolecularTransformer/experiments/models/ofs_1.pt).Feel free to email me, Daniel Wigh, at dsw46@cam.ac.uk or daniel@reactwise.com or my supervisor Alexei A. Lapkin.
DOI: 10.15468/dl.b2aq5c
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:ADE2269"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010217-250711103210423/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.29552543.v3
title: ORDerly Transformer Models for chemical tasks

description: Transformer models trained on tasks in organic chemistry on ORDerly benchmark datasets.ORDerly_retro: Retrosynthesis prediction (prediction reactants given a desired product)ORDerly_forward_separated: Forward reaction prediction (predict reaction products given reactants, solvents, and agents), with reactants separated by &gt; from the solvents and agents in the reaction string.ORDerly_forward_mixed: Forward reaction prediction (predict reaction products given reactants, solvents, and agents), with reactants, solvents and agents mixed together in the reaction string.non-uspto-eval: Evaluation of transformer models trained on USPTO data on non-uspto data available in the Open Reaction Database.Full details can be found in our paper: https://chemrxiv.org/engage/chemrxiv/article-details/64ca5d3e4a3f7d0c0d78ca42Neurips workshop paper: https://openreview.net/forum?id=R8FQMsECISCode: https://github.com/sustainable-processes/orderlyThe supplementary datasets used for this work can be found here: https://doi.org/10.6084/m9.figshare.23502372.v3Transformer model architecture is from Molecular Transformer: https://pubs.acs.org/doi/10.1021/acscentsci.9b00576Find the results, models, and checkpoints within MolecularTransformer/experiments. Note that the "wandb" folder was deleted since figshare only allows uploads up to 500 files.Notes:There's a limit of 500 files in figshare, so I deleted the the "docs" and "onmt", and "OpenNMT_py.egg-info" , and "tools" folders from all folders except "ORDerly_retro". I also deleted all wandb-associated files and all checkpoint files.Empty files cannot be uploaded to figshare, so you have to create these yourself, where appropriate (e.g. MolecularTransformer/onmt/tests/__init__.py and non-uspto-eval/MolecularTransformer/experiments/models/ofs_1.pt).Feel free to email me, Daniel Wigh, at dsw46@cam.ac.uk or daniel@reactwise.com or my supervisor Alexei A. Lapkin.
DOI: 10.6084/m9.figshare.23766477.v7
title: HAM10000 expert-annotated explanations and pseudonymized reader study data.

description: Reader study was conducted in 3 phases: no ai (phase 1), ai support (phase 2), xai support (phase 3). The data generated in each phase is available in metadata_phase1.csv, metadata_phase2.csv, and metadata_phase3.csv.There are 113 unique participants in phase 1. Additional participants were added in phase 2, resulting in 116 unique clinicians in phases 2 and 3.<b>Important:</b> The 3rd and 13th image in each group are identical. Be careful when performing table joins as the duplicate image_ids can affect them. In metadata_phase1.csv, the AI predictions for the 13th image in each group are null. Please take that into account when performing analysis. In metadata_phase2 and metadata_phase3, the AI predictions for the repeating images are not omitted.<br><i>participant</i>: Each clinician was assigned a participant Id represented by the participant column.<i>group</i>: Each clinician was randomly assigned to a group. Each group was assigned mutually exclusive sets of images.<i>mask</i>: An internal identifier used for the images. Can be ignored.<i>benign_malignant</i>: ground truth diagnosis.<i>prediction</i>: Diagnosis chosen by the clinician. 1 represents melanoma, 0 represents nevus, 0.5 represents a nevus diagnosis but the clinician chose to excise.<i>confidence</i>: Confidence value entered by the clinician.<i>trust</i>: Trust value entered by the clinician.<i>AI_prediction</i>: Diagnosis predicted by the AI. 1 represents melanoma and 0 represents nevus. <i>language</i>: Language chosen by the clinician.
DOI: 10.15468/dl.wqmpfu
title: Occurrence Download

description: A dataset containing 301 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bauhinia japonica"
 ]
}

 The dataset includes 301 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010218-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/262q-st17
title: "Expeience the best Mallorca\u2019s Underwater Wonders with Petro Divers"

description: "Petro Divers welcomes you to experience that thrill of best cave diving Mallorca, Spain, with custom personal underwater tours for everyone. Our experienced trainers will ensure your dive is safe, fun, and educational each time. You can discover Mallorca\u00b4s stunning cave formations with the latest gear in a personal tour with the attention of our trainers. Palestine Torres will provide professional cursos de buceo mallorca as part of our expert dive center. We can ensure you can wenjoy personalized diving whether you are a rookie or an experienced diver. With Petro Divers you receive the best possible service to ensure your diving experience is personal.Get In TouchAddress: Calo des Moix 8, 07691 Porto Petro, I. Baleares, Espa\u00f1aPhone : +34 682 28 03 94E-mail: info@petrodivers.com"
DOI: 10.15468/dl.aeqjxs
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudorasbora parva",
 "Country is Montenegro",
 "HasCoordinate is true"
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010219-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pa44d4
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cyrtandra bracheia"
 ]
}

 The dataset includes 74 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010220-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8dw8n9
title: Occurrence Download

description: A dataset containing 1571 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudorasbora parva",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1571 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010221-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wpdaxj
title: Occurrence Download

description: A dataset containing 308 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hyptis lacustris"
 ]
}

 The dataset includes 308 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010222-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bdbrfh
title: Occurrence Download

description: A dataset containing 136 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lantana camara",
 "Country is Cabo Verde",
 "HasCoordinate is true"
 ]
}

 The dataset includes 136 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010223-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/q1ioj5
title: Archeologisch bureauonderzoek Houtsestraat 14-16 te Puiflijk, gemeente Druten (GD)

description: Laagland Archeologie heeft in april 2025 een Archeologisch bureauonderzoek uitgevoerd aan de Houtsestraat 14-16 te Puiflijk. Het onderzoek vond plaats in verband met de ruimtelijke procedure rondom de nieuwbouw van woningen.
Het onderzoek is uitgevoerd conform protocol SIKB KNA 4002.
Het bureauonderzoek had tot doel een archeologisch verwachtingsmodel op te stellen. Centraal staat daarbij de vraag of en zo ja welke archeologische resten (complextype, datering, diepteligging en gaafheid) in het plangebied kunnen worden verwacht. Hiertoe zijn landschappelijke, archeologische en historische bronnen geraadpleegd.
Op basis van eerder onderzoek waarvan een booronderzoek in het plangebied en gravend onderzoek in de directe omgeving waar resten vanaf de IJzertijd tot Nieuwe Tijd zijn aangetroffen, waaronder mogelijk resten van steenbouw (romeins beton) uit de Romeinse Tijd) wordt nader archeologisch onderzoek geadviseerd conform protocol 4003 IVO (landbodems). Op basis van het aangetroffen aardewerk bij een karterend booronderzoek op ongeveer de grootste zuidwestelijke helft van het plangebied worden in dat deel in ieder geval bewoningssporen verwacht uit de Vroege/Midden-IJzertijd tot en met de Middeleeuwen.
Gelet op de te verwachten prospectiekenmerken en prospecteerbaarheid van een eventuele vindplaats wordt geadviseerd dit vervolgonderzoek uit te voeren in de vorm van een proefsleuvenonderzoek conform de KNA Leidraad Inventariserend Veldonderzoek Deel: Proefsleuvenonderzoek (IVO-P). Hiervoor is een door het bevoegd gezag goed te keuren Programma van Eisen benodigd. Omdat delen van het plangebied verstoord kunnen zijn, verdiend het wel aanbeveling om een verkennend booronderzoek uit te voeren, voordat een proefsleuvenonderzoek wordt uitgevoerd. Hiermee kunnen bepaalde diep verstoorde zones worden uitgesloten en kunnen mogelijk kosten worden uitgespaard.
Dit advies is overgenomen door de bevoegde overheid, de gemeente Druten. De gemeente wordt hierin vertegenwoordigd door haar deskundige, mevrouw Ester van der Linden.