cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/n4jn62rh2m.1
title: Supplementary Materials for Optimizing Real-Time Phenotyping in Critical Care Using Machine Learning on Electronic Health Records

description: This dataset accompanies the study "Optimizing Real-Time Phenotyping in Critical Care Using Machine Learning on Electronic Health Records," which hypothesizes that a patient's latent disease state can be continuously and accurately estimated from real-time biomedical signals without requiring full ICU trajectories. It supports replication and evaluation of our predictive framework, which dynamically models phenotype probabilities as data accumulates. All elements are reported in line with the TRIPOD statement to ensure transparency and reproducibility.

The training and test data are derived from the MIMIC-IV database and consist of vectorized representations of multivariate, irregularly sampled biomedical time series and associated phenotype labels. These were generated through a structured pipeline that includes cohort selection, event aggregation using fixed-length time bins, and feature engineering to represent both value trends and missingness. Supplementary Tables S.1 to S.6 describe the variables used in this transformation, their sources within the EHR, aggregation methods, and descriptive statistics for both static (e.g., demographics, admission data) and dynamic (e.g., vital signs, lab results, ventilator settings) features across the train and test sets.

Table S.7 summarizes the model’s real-time phenotyping performance using multiple evaluation perspectives. The results reveal strong generalization and early predictive value: in the (ls) setting, the model achieved good diagnostic performance (AUROC ≥ 0.8) for 69% of phenotypes and excellent performance (AUROC ≥ 0.9) for 30%. In the real-time (fs) setting—using only the earliest recorded physiological data—the model still achieved good performance for 40% of phenotypes and excellent performance for 5%, demonstrating the feasibility of early, actionable phenotyping. The intermediate (td) evaluation shows that predictive quality improves consistently as more data becomes available, supporting the framework’s ability to track dynamic disease progression in real time.

To interpret and use the data:
- Each patient stay is represented as a multivariate time series with associated phenotype labels.
- Time series are aligned in fixed time intervals (e.g., 2 hours), where each variable is aggregated using statistical functions (e.g., mean, last, sum).
- The phenotype labels correspond to ICD-9-CM diagnostic categories assigned at discharge but are used here as latent variables to be estimated continuously.

This dataset enables reproducibility of the results and further research in developing machine learning models for early, interpretable, and actionable phenotyping in critical care.
DOI: 10.3535/7jq-5n2-vym
title: Salix starkeana Willd.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vgs-cv0-tdt
title: Cenchrus purpureus (Schumach.) Morrone

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/z3w-g7a-tk4
title: Halopyrum mucronatum (L.) Stapf

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.xnept8
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cajanus cajan",
 "Country is Cook Islands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068402-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/623-qwp-43y
title: Salix repens subsp. repens

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8vc-k7c-y7j
title: Salix repens subsp. repens

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/2lh-yck-gbs
title: Lepidium uzbekistanicum Al-Shehbaz

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/jk0-5ae-j1s
title: Lepidium costaricense Thell.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/cyd-lrt-cb5
title: Potamogeton obtusifolius Mert. & W.D.J.Koch

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/rlp-qx9-6vv
title: Lepidium altissimum Rech. fil.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.17632/frwny8tmbj
title: Supplementary Data for "Structural architecture of the Cenozoic Kallianos (post-?)orogenic vein-hosted Au-Ag-Te deposit and its relationship to the North Cycladic Detachment System, Greece"

description: Supporting figures and tables for G-Cubed article "Structural architecture of the Cenozoic Kallianos (post-?)orogenic vein-hosted Au-Ag-Te deposit and its relationship to the North Cycladic Detachment System, Greece" by L. Hamel and co-authors.
DOI: 10.3535/bd6-mjh-6c8
title: Potamogeton trichoides Cham. & Schltdl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/mcb-dw8-vrj
title: Potamogeton trichoides Cham. & Schltdl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/zjq-smk-qxr
title: Potamogeton perfoliatus L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.rb5xpa
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cajanus cajan",
 "Country is Eswatini",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068403-250717081556266/datasets/export for details.
DOI: 10.17632/frwny8tmbj.1
title: Supplementary Data for "Structural architecture of the Cenozoic Kallianos (post-?)orogenic vein-hosted Au-Ag-Te deposit and its relationship to the North Cycladic Detachment System, Greece"

description: Supporting figures and tables for G-Cubed article "Structural architecture of the Cenozoic Kallianos (post-?)orogenic vein-hosted Au-Ag-Te deposit and its relationship to the North Cycladic Detachment System, Greece" by L. Hamel and co-authors.
DOI: 10.3535/1db-kkd-kcg
title: Salix myrsinifolia Salisb.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vvt-a2z-3mz
title: Salix pedicellata Desf.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/sb2-2la-ybk
title: Campanula fenestrellata subsp. debarensis (Rech.f.) Damboldt

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/tv6-57r-l93
title: Robiquetia spathulata (Blume) J.J.Sm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.7910/dvn/lsx6fd
title: Climate Security Programming Dashboard for Climate Finance (CSPDxCF): dataset on compound risk exposure

description: Developed to support the Climate Security Programming Dashboard for Climate Finance (CSPDxCF), an all-in-one solution for preliminary conflict-sensitive assessments and tailored guidance, targeting projects funded by international financial institutions and climate funds. See CSPD website for more details (https://cspd.cso.cgiar.org)
&lt;br&gt;&lt;br&gt; 
Methodology: Reference Methodology: https://cgspace.cgiar.org/items/0e89c5ec-b958-4f90-90ae-71ac8b472def Changelog (data button): https://cspd.cso.cgiar.org/about
DOI: 10.34740/kaggle/dsv/11970637
title: Diatom algae colorized Dataset
DOI: 10.15468/dl.pknswf
title: Occurrence Download

description: A dataset containing 30608 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Chloropicon laureae Santos & Eikrem, 2017, Plagioselmis prolonga Butcher, Teleaulax amphioxeia (Conrad) Hill, 1992, Dinophysis acuminata Claparède & Lachmann, Ceratium carriense Gourret, 1883, Tripos contrarius (Gourret) F.Gómez, Tripos furca (Ehrenb.) F.Gómez, Tripos fusus (Ehrenb.) F.Gómez, Ceratium hexacanthum Gourret, Protoceratium reticulatum (Claparède & Lachmann) Bütschli, 1885, Alexandrium affine (H.Inoue & Y.Fukuyo) Balech, 1995, Alexandrium margalefii Balech, Pseliodinium fusus (F.Schütt) F.Gómez, 2018, Gymnodinium heterostriatum Kofoid & Swezy, 1921, Karlodinium veneficum (D.Ballant.) J.Larsen, Noctiluca scintillans (Macartney) Kof. & Swezy, Protoperidinium depressum (J.W.Bailey) Balech, 1974, Karlodinium micrum (B.Leadb. & J.D.Dodge) J.Larsen, Prorocentrum micans Ehrenberg, 1833, Goniodoma polyedricum (Pouchet) E.Jørgensen, 1900, Gephyrocapsa oceanica Kamptner, Pseudo-nitzschia calliantha Lundholm, Moestrup & Hasle, 2003, Pinnularia appendiculata (C.Agardh) Cleve, Navicula membranacea Cleve, 1897, Bacteriastrum hyalinum Lauder, Chaetoceros dayaensis Li & Zhu, 2015, Chaetoceros costatus Pavillard, Chaetoceros danicus Cleve, Chaetoceros decipiens Cleve, Chaetoceros lauderi Ralfs, Chaetoceros rostratus Lauder, Chaetoceros socialis Lauder, Chaetoceros tenuissimus Meunier, Leptocylindrus convexus D.Nanjappa & A.Zingone, 2013, Leptocylindrus hargravesii D.Nanjappa & A.Zingone, 2013, Stephanopyxis turris (Greville) Ralfs, 1861, Rhizosolenia flaccida Castracane, 1886, Guinardia striata Hensen, 1911, Rhizosolenia delicatula Cleve, 1900, Rhizosolenia fallax B.G.Sundström, 1986, Minidiscus comicus Takano, 1981, Cerataulina bergonii Ostenfeld, 1903, Hemiaulus sinensis Greville, 1865)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((27.52482 41.74366,22.83195 41.29672,21.93807 39.06202,20.37378 42.1906,12.80438 46.46699,6.85384 44.4253,2.50779 43.58318,2.2727 42.30233,-0.07373 40.73804,-1.30282 38.61508,-2.97885 37.60946,-5.66049 37.16252,-5.77222 34.92782,-0.96761 34.25741,3.94873 35.70997,9.08854 36.04517,9.75895 33.25179,11.77018 32.13444,13.55794 31.57577,19.8151 29.34107,21.7146 31.79924,28.75391 30.12321,31.10034 30.34668,34.89933 30.23495,37.0223 36.93905,30.3182 37.27426,27.97176 38.0564,27.52482 39.39722,29.75952 40.40284,27.52482 41.74366))"
 ]
}

 The dataset includes 30608 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003261-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15525227
title: Connectivity via resource flows interacts with ecosystem size and disturbance to affect meta-ecosystem function

description: Data & code for the paper "Connectivity via resource flows interacts with ecosystem size and disturbance to affect meta-ecosystem function".
DOI: 10.5281/zenodo.15526431
title: Connectivity via resource flows interacts with ecosystem size and disturbance to affect meta-ecosystem function

description: Data & code for the paper "Connectivity via resource flows interacts with ecosystem size and disturbance to affect meta-ecosystem function".
DOI: 10.15468/dl.tfbte5
title: Occurrence Download

description: A dataset containing 128 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Philippines",
 "OccurrenceStatus is Present",
 "TaxonKey is Triaenodon obesus (Rüppell, 1837)"
 ]
}

 The dataset includes 128 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003259-250525065834625/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.28915592
title: Panel Data_Rem_2002_2023_12.04.2025.xlsx

description: The paper examines the impact of remittances on nominal GDP growth in six Western Asian countries: Armenia, Georgia, Cyprus, Egypt, Turkey, and Azerbaijan. Based on annual data for the period 2002-2023, panel data models were built. The Two-Stage Least Squares (TSLS) method was used to eliminate the endogeneity problem. The estimation results show that remittances have a positive statistically significant impact on GDP. According to the Random Effects model, a 1% increase in remittances contributes to a 0.28% increase in GDP.<br>
DOI: 10.15156/bio/sh1387783.10fu
title: SH1387783.10FU

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/sh1387784.10fu
title: SH1387784.10FU

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/sh1387785.10fu
title: SH1387785.10FU

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/sh1387786.10fu
title: SH1387786.10FU

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/sh1387787.10fu
title: SH1387787.10FU

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/sh1387788.10fu
title: SH1387788.10FU

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/sh1387791.10fu
title: SH1387791.10FU

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/sh1387795.10fu
title: SH1387795.10FU

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/sh1387796.10fu
title: SH1387796.10FU

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/sh1387797.10fu
title: SH1387797.10FU

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.