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

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brunia noduliflora Goldblatt & J.C.Manning",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((30.5701 -24.0715,25.5395 -24.0715,25.5395 -28.5786,30.5701 -28.5786,30.5701 -24.0715))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050698-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aadbq2
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Philippines",
 "TaxonKey is Petinomys crinitus (Hollister, 1911)"
 ]
}

 The dataset includes 25 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050699-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yx959v
title: Occurrence Download

description: A dataset containing 4988 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Biological observations from the Dana Expedition Reports"
 ]
}

 The dataset includes 4988 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050700-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15358476
title: Migration Mobility Survey, Survey on living as a migrant in Switzerland 2016-2018-2020-2022-2024

description: Migration Mobility Survey, waves 2016, 2018, 2020, 2022 and 2024. Codebook and metadata along DDI standard.

Statistical files in csv, sav and dta format

The fifth wave of the Migration-Mobility Survey took place during the fall of 2024.6971 migrants were surveyed, 3437 of whom were surveyed 2 years ago (Panel).The remaining 3534 comprised the so-called Refresh sample.
DOI: 10.15468/dl.md92ub
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Philippines",
 "TaxonKey is Petinomys mindanensis (Rabor, 1939)"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050701-250525065834625/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.29336063
title: Vehicle trajectories and in-vehicle video data

description: Vehicle trajectories and in-vehicle video data in six different traffic scenarios.
DOI: 10.6084/m9.figshare.29336063.v1
title: Vehicle trajectories and in-vehicle video data

description: Vehicle trajectories and in-vehicle video data in six different traffic scenarios.
DOI: 10.15468/dl.sr4haw
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Entomology Division, Yale Peabody Museum",
 "Country is Croatia"
 ]
}

 The dataset includes 29 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050702-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9xjt5x
title: Occurrence Download

description: A dataset containing 647 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Lund University Biological Museum - Insect collections Inventory",
 "Country is Croatia"
 ]
}

 The dataset includes 647 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050703-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g6s36g
title: Occurrence Download

description: A dataset containing 384622 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Juncus alpinoarticulatus Chaix, Poa glauca Vahl, Prunus padus L., Ranunculus platanifolius L., Saxifraga cotyledon L.)",
 "Geometry POLYGON ((-180 45.53015, 180 45.53015, 180 83.62313, -180 83.62313, -180 45.53015))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "CoordinateUncertaintyInMeters is less than or equal to 50000"
 ]
}

 The dataset includes 384622 records from 620 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050682-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fkht7r
title: Occurrence Download

description: A dataset containing 77 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Philippines",
 "TaxonKey is Hylopetes nigripes (Thomas, 1893)"
 ]
}

 The dataset includes 77 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050704-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6jupsr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brunia noduliflora Goldblatt & J.C.Manning",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((27.1332 -20.158,25.5395 -23.2724,25.5395 -24.0715,30.5701 -24.0715,30.5701 -20.3186,29.6496 -19.6123,28.947 -19.4003,28.1821 -19.4609,27.6072 -19.7214,27.1332 -20.158))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050705-250525065834625/datasets/export for details.
DOI: 10.15468/dl.np3t64
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is CAS Invertebrate Zoology (IZ)",
 "Country is Croatia"
 ]
}

 The dataset includes 15 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050706-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x2amt6
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is NSW AVH feed",
 "Country is Croatia"
 ]
}

 The dataset includes 10 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050707-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t5463r
title: Occurrence Download

description: A dataset containing 5343 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is INSDC Sequences",
 "Country is Croatia"
 ]
}

 The dataset includes 5343 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050708-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fvqrd
title: Occurrence Download

description: A dataset containing 392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brunia noduliflora Goldblatt & J.C.Manning",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((25.0214 -34.0501,25.5395 -34.1098,25.5395 -32.9007,20.509 -32.9007,20.509 -34.5676,20.524 -34.555,20.8859 -34.5419,20.9606 -34.4398,21.2995 -34.5131,21.5296 -34.4338,21.8696 -34.4439,22.0323 -34.2835,22.221 -34.2428,22.2566 -34.1304,22.5993 -34.0741,22.9652 -34.1674,23.4069 -34.1858,23.4955 -34.0792,23.6056 -34.0563,24.8471 -34.2877,24.9447 -34.2397,25.0214 -34.0501))"
 ]
}

 The dataset includes 392 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050710-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cq95pn
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is UF FLMNH Ichthyology",
 "Country is Croatia"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050712-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j4rbyh
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Lichen herbarium TRH, NTNU University Museum",
 "Country is Croatia"
 ]
}

 The dataset includes 102 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050716-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ma9b6
title: Occurrence Download

description: A dataset containing 634 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bambusa multiplex (Lour.) Raeusch. ex Schult.f.",
 "Year 1739-2025"
 ]
}

 The dataset includes 634 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050713-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dhvtxr
title: Occurrence Download

description: A dataset containing 4737 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lagocephalus sceleratus (Gmelin, 1789)"
 ]
}

 The dataset includes 4737 records from 118 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050717-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tjxecr
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Biofokus",
 "Country is Croatia"
 ]
}

 The dataset includes 25 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050715-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v4z9e6
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Western Australian Herbarium (PERTH) AVH data",
 "Country is Croatia"
 ]
}

 The dataset includes 9 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050719-250525065834625/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.29336318
title: Supplementary Material for: Using Machine learning to predict medication therapy problems among patients with chronic kidney disease

description: Introduction: Patients with chronic kidney disease (CKD) are at risk of medication therapy problems (MTP) due to high comorbidity and medication burden. Using data from the Kidney Coordinated HeAlth Management Partnership (Kidney CHAMP) trial, we used machine learning to build a predictive model to identify MTP high-risk patients with CKD in the primary care setting.
Methods: We used baseline data from patients enrolled in the intervention arm of the Kidney CHAMP trial, completed May 2019 to July 2022, which tested a population health management strategy, including medication management, for improving CKD care. The dataset was divided into 80% training and 20% testing subsets. The area under the ROC curve (AUROC) was used to assess classification accuracy in distinguishing between patients with and without MTP. Eight candidate models were considered, and the top three performing models (Random Forest, Support Vector Machines, and Gradient Boosting), based on cross-validated AUROC on training data, underwent further refinement. The model with the highest AUROC in the testing set, while considering the bias/variance trade-off, was selected as the best-performing model. SHapley Additive exPlanations (SHAP) was then leveraged using the best-performing model to evaluate the impact of each predictor to the final risk score.
Results: Among 730 patients who received medication review at baseline, 566 (77.5%) had at least 1 MTP. Key demographics were mean age 74 years, 55% females, 92% White, 64% with diabetes, and the mean number of medications was 5.8 at baseline. The Random Forest model had the best performance on the testing set with AUROC 0.72, sensitivity 0.80, and specificity 0.64. The five most influential variables, ranked in descending order of importance for predicting individuals with MTP, were diabetes status (yes/no), hemoglobin A1C (HbA1C), urine albumin-to-creatinine ratio (UACR), systolic blood pressure, and age.
Conclusion: In outpatient primary care, a machine learning-based MTP risk calculator that use routinely available clinical data can identify patients with moderate-high risk CKD who are at high risk for developing MTPs.
DOI: 10.6084/m9.figshare.29336318.v1
title: Supplementary Material for: Using Machine learning to predict medication therapy problems among patients with chronic kidney disease

description: Introduction: Patients with chronic kidney disease (CKD) are at risk of medication therapy problems (MTP) due to high comorbidity and medication burden. Using data from the Kidney Coordinated HeAlth Management Partnership (Kidney CHAMP) trial, we used machine learning to build a predictive model to identify MTP high-risk patients with CKD in the primary care setting.
Methods: We used baseline data from patients enrolled in the intervention arm of the Kidney CHAMP trial, completed May 2019 to July 2022, which tested a population health management strategy, including medication management, for improving CKD care. The dataset was divided into 80% training and 20% testing subsets. The area under the ROC curve (AUROC) was used to assess classification accuracy in distinguishing between patients with and without MTP. Eight candidate models were considered, and the top three performing models (Random Forest, Support Vector Machines, and Gradient Boosting), based on cross-validated AUROC on training data, underwent further refinement. The model with the highest AUROC in the testing set, while considering the bias/variance trade-off, was selected as the best-performing model. SHapley Additive exPlanations (SHAP) was then leveraged using the best-performing model to evaluate the impact of each predictor to the final risk score.
Results: Among 730 patients who received medication review at baseline, 566 (77.5%) had at least 1 MTP. Key demographics were mean age 74 years, 55% females, 92% White, 64% with diabetes, and the mean number of medications was 5.8 at baseline. The Random Forest model had the best performance on the testing set with AUROC 0.72, sensitivity 0.80, and specificity 0.64. The five most influential variables, ranked in descending order of importance for predicting individuals with MTP, were diabetes status (yes/no), hemoglobin A1C (HbA1C), urine albumin-to-creatinine ratio (UACR), systolic blood pressure, and age.
Conclusion: In outpatient primary care, a machine learning-based MTP risk calculator that use routinely available clinical data can identify patients with moderate-high risk CKD who are at high risk for developing MTPs.
DOI: 10.6084/m9.figshare.29336321
title: Supplementary Material for: Assessing Rural Veterans’ Experiences with a Tele-Nephrology Program in the Veterans Health Administration (VHA)

description: Introduction: Rural living Veterans with chronic kidney disease (CKD) and refractory hypertension (rHTN) have a higher mortality rate and are hospitalized more frequently than Veterans living in urban or suburban areas. They also face particularly unique challenges in accessing nephrology specialty care. Previous studies suggest virtual nephrology care can be used to increase access to care for Veterans. The purpose of this study was to examine Veteran’s perceptions and experiences with a VA virtual nephrology program. 
Methods: We conducted semi-structured interviews with forty-four Veterans at five rural VA medical centers who were receiving virtual nephrology care (“tele-nephrology”).
Results: Four major themes arose that represent the Veterans’ perceptions and experiences with VA virtual nephrology care: 1) Tele-nephrology provides timely access to care for Veterans living in rural areas; 2) Clinical partnerships between primary care and tele-nephrology are key to Veterans’ health; 3) Veterans’ technology fears were assuaged with virtual nephrology care; 4) Improvements to care include more direct access to virtual nephrologists. 
Conclusion: This evaluation represents an important step forward in how the VA can enhance virtual nephrology care to better meet the needs of rural Veterans receiving care at facilities without VA specialty providers. Prior to the Choice and MISSION Acts, Veterans were often required to drive long distances to the closest VA specialty provider. However, since the COVID-19 pandemic, the VA has been shifting care from community to VA via virtual care. Further research should examine Veterans’ experiences with both different modalities of nephrology care as well as experiences from demographically and geographically diverse Veterans.
DOI: 10.6084/m9.figshare.29336321.v1
title: Supplementary Material for: Assessing Rural Veterans’ Experiences with a Tele-Nephrology Program in the Veterans Health Administration (VHA)

description: Introduction: Rural living Veterans with chronic kidney disease (CKD) and refractory hypertension (rHTN) have a higher mortality rate and are hospitalized more frequently than Veterans living in urban or suburban areas. They also face particularly unique challenges in accessing nephrology specialty care. Previous studies suggest virtual nephrology care can be used to increase access to care for Veterans. The purpose of this study was to examine Veteran’s perceptions and experiences with a VA virtual nephrology program. 
Methods: We conducted semi-structured interviews with forty-four Veterans at five rural VA medical centers who were receiving virtual nephrology care (“tele-nephrology”).
Results: Four major themes arose that represent the Veterans’ perceptions and experiences with VA virtual nephrology care: 1) Tele-nephrology provides timely access to care for Veterans living in rural areas; 2) Clinical partnerships between primary care and tele-nephrology are key to Veterans’ health; 3) Veterans’ technology fears were assuaged with virtual nephrology care; 4) Improvements to care include more direct access to virtual nephrologists. 
Conclusion: This evaluation represents an important step forward in how the VA can enhance virtual nephrology care to better meet the needs of rural Veterans receiving care at facilities without VA specialty providers. Prior to the Choice and MISSION Acts, Veterans were often required to drive long distances to the closest VA specialty provider. However, since the COVID-19 pandemic, the VA has been shifting care from community to VA via virtual care. Further research should examine Veterans’ experiences with both different modalities of nephrology care as well as experiences from demographically and geographically diverse Veterans.
DOI: 10.15468/dl.b4ryq8
title: Occurrence Download

description: A dataset containing 5066 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((14.879505796264475 48.604057880322166, 15.061305867958408 48.59591473877061, 15.073657373928532 48.71743082918659, 14.891417042594657 48.72559684748014, 14.879505796264475 48.604057880322166))"
 ]
}

 The dataset includes 5066 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050718-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nrb284
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Triplehorn Insect Collection, The Ohio State University",
 "Country is Croatia"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050720-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5n29pk4b
title: MassIVE MSV000098229 - GNPS_GC_ProspecTER_Biofilm extracts_20250617_Sara Finnerty
title: GC-MS profiling of crude lipid extracts from intertidal microphytobenthic biofilms from the coasts of Ireland. Freeze-dried biofilm (5-10 g) was extracted via ultrasonication-assisted extraction with dichloromethane:methanol (1:1, v/v, 30 mL x 3 cycles). Crude extracts were derivatised with sodium methoxide (NaOMe) and N,O-Bis(trimethylsilyl)trifluoroacetamide with trimethylchlorosilane (BSTFA/TMCS). Analysed via GC-MS in pyridine on a HP-5MS column.
DOI: 10.34810/data319
title: Esperanto-French LMF Apertium Bilingual dictionary

description: This is the LMF version of the Apertium bilingual dictionary for Esperanto and French languages. Bilingual LMF dictionaries were generated from Apertium bilingual dix files. For each Apertium bilingual correspondence, the corresponding source and target monolingual entries (LexicalEntry) were generated in addition to the bilingual correspondence (SenseAxis) element. Apertium is a free/open-source machine translation platform, initially aimed at related-language pairs but recently expanded to deal with more divergent language pairs (such as Esperanto-French). The platform provides: a language-independent machine translation engine; tools to manage the linguistic data necessary to build a machine translation system for a given language pair and linguistic data for a growing number of language pairs.
DOI: 10.15468/dl.skbtnz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brunia noduliflora Goldblatt & J.C.Manning",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((32.064 -28.9416,32.4847 -28.5786,30.5701 -28.5786,30.5701 -30.7329,30.6252 -30.6659,31.4179 -29.4257,31.8178 -29.0299,32.064 -28.9416))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050722-250525065834625/datasets/export for details.