cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/cc6096p
title: CCDC 179031: Experimental Crystal Structure Determination

description: Related Article: M.B.Ferrari, C.Pelizzi, G.Pelosi, M.C.Rodriguez-Arguelles|2002|Polyhedron|21|2593|doi:10.1016/S0277-5387(02)01234-2
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/cc65mkj
title: CCDC 184157: Experimental Crystal Structure Determination

description: Related Article: T.J.Davis, P.J.Carroll, P.J.Walsh|2002|J.Organomet.Chem.|663|70|doi:10.1016/S0022-328X(02)01656-X
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/cc65mlk
title: CCDC 184158: Experimental Crystal Structure Determination

description: Related Article: T.J.Davis, P.J.Carroll, P.J.Walsh|2002|J.Organomet.Chem.|663|70|doi:10.1016/S0022-328X(02)01656-X
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/cc65mml
title: CCDC 184159: Experimental Crystal Structure Determination

description: Related Article: T.J.Davis, P.J.Carroll, P.J.Walsh|2002|J.Organomet.Chem.|663|70|doi:10.1016/S0022-328X(02)01656-X
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/cc686qc
title: CCDC 186642: Experimental Crystal Structure Determination

description: Related Article: J.Gimeno, E.Lastra, C.Madrigal, C.Graiff, A.Tiripicchio|2002|J.Organomet.Chem.|663|204|doi:10.1016/S0022-328X(02)01963-0
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/cc686rd
title: CCDC 186643: Experimental Crystal Structure Determination

description: Related Article: J.Gimeno, E.Lastra, C.Madrigal, C.Graiff, A.Tiripicchio|2002|J.Organomet.Chem.|663|204|doi:10.1016/S0022-328X(02)01963-0
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/cc696qd
title: CCDC 187603: Experimental Crystal Structure Determination

description: Related Article: J.A.Cabeza, I.del Rio, S.Garcia-Granda, L.Martinez-Mendez, V.Riera|2002|J.Organomet.Chem.|663|227|doi:10.1016/S0022-328X(02)01777-1
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/cc696rf
title: CCDC 187604: Experimental Crystal Structure Determination

description: Related Article: J.A.Cabeza, I.del Rio, S.Garcia-Granda, L.Martinez-Mendez, V.Riera|2002|J.Organomet.Chem.|663|227|doi:10.1016/S0022-328X(02)01777-1
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/cc69nqv
title: CCDC 188037: Experimental Crystal Structure Determination

description: Related Article: I.Ara, L.R.Falvello, J.Fornies, J.Gomez-Cordon, E.Lalinde, R.I.Merino, I.Uson|2002|J.Organomet.Chem.|663|284|doi:10.1016/S0022-328X(02)01991-5
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.twm7a3
title: Occurrence Download

description: A dataset containing 844 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bolusafra bituminosa)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 844 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014919-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ttbgjr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Solenogastres)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((170 10,180 10,180 20,170 20,170 10))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014920-251009101135966/datasets/export for details.
DOI: 10.15468/dl.96uysu
title: Occurrence Download

description: A dataset containing 644 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen, Occurrence evidence)",
 "Geometry POLYGON((-142.30336 23.27208,-78.69664 23.27208,-78.69664 48.72792,-142.30336 48.72792,-142.30336 23.27208))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Libellula composita"
 ]
}

 The dataset includes 644 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014921-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sw8qad
title: Occurrence Download

description: A dataset containing 988 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cephalopoda)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((110 -10,120 -10,120 0,110 0,110 -10))"
 ]
}

 The dataset includes 988 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014922-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9mkb9f
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Solenogastres)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((160 10,170 10,170 20,160 20,160 10))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014923-251009101135966/datasets/export for details.
DOI: 10.15468/dl.f29ee2
title: Occurrence Download

description: A dataset containing 4370 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oenothera gaura"
 ]
}

 The dataset includes 4370 records from 187 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014924-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17054383
title: HPLC data from South-Western Black Sea, September 2021

description: The dataset contains HPLC data collected in South-Western Black Sea withing the Turkish EEZ in September 2021 during the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project.

Discrete water samples were taken with Niskin bottles (12 L capacity) at depths, that were selected according to water density profiles. The CTD rosette with Niskin bottles was kept for at least 2 minutes at each sampling depth. The samples were analized in METU-IMS lab upon completing the cruise. The data file in ODV format contains data from 25 stations.
DOI: 10.5281/zenodo.17054382
title: HPLC data from South-Western Black Sea, September 2021

description: The dataset contains HPLC data collected in South-Western Black Sea withing the Turkish EEZ in September 2021 during the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project.

Discrete water samples were taken with Niskin bottles (12 L capacity) at depths, that were selected according to water density profiles. The CTD rosette with Niskin bottles was kept for at least 2 minutes at each sampling depth. The samples were analized in METU-IMS lab upon completing the cruise. The data file in ODV format contains data from 25 stations.
DOI: 10.6084/m9.figshare.29980583
title: Variational Inference Aided Variable Selection For Spatially Structured High Dimensional Covariates

description: We consider the problem of Bayesian high dimensional variable selection in linear regression when a spatial structure exists among the covariates. We use an Ising prior to model the structural connectivity of the covariates with an undirected graph and the connectivity strength with Ising distribution parameters. Ising models, which originated in statistical physics, are widely used in computer vision and spatial data modeling. Although a Gibbs solution to this problem exists, the solution involves the computation of determinants and inverses of high dimensional matrices, rendering it unscalable to higher dimensions. Furthermore, the lack of theoretical support limits this important tool’s use for the broader community. This article proposes a variational inference-aided Gibbs approach that enjoys the same variable recovery power as the standard Gibbs solution while being computationally scalable to higher dimensions. We establish strong selection consistency for our proposed approach, along with its competitive numerical performance under varying simulation scenarios. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.29980583.v1
title: Variational Inference Aided Variable Selection For Spatially Structured High Dimensional Covariates

description: We consider the problem of Bayesian high dimensional variable selection in linear regression when a spatial structure exists among the covariates. We use an Ising prior to model the structural connectivity of the covariates with an undirected graph and the connectivity strength with Ising distribution parameters. Ising models, which originated in statistical physics, are widely used in computer vision and spatial data modeling. Although a Gibbs solution to this problem exists, the solution involves the computation of determinants and inverses of high dimensional matrices, rendering it unscalable to higher dimensions. Furthermore, the lack of theoretical support limits this important tool’s use for the broader community. This article proposes a variational inference-aided Gibbs approach that enjoys the same variable recovery power as the standard Gibbs solution while being computationally scalable to higher dimensions. We establish strong selection consistency for our proposed approach, along with its competitive numerical performance under varying simulation scenarios. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.29916753
title: Nonparametric Assessment of Variable Selection and Ranking Algorithms

description: Selecting from or ranking a set of candidate variables in terms of their capacity for predicting an outcome of interest is an important task in many scientific fields. A variety of methods for variable selection and ranking have been proposed in the literature. In practice, it can be challenging to know which method is most appropriate for a given dataset. In this article, we propose methods of comparing variable selection and ranking algorithms. We first introduce measures of the quality of variable selection and ranking algorithms. We then define estimators of our proposed measures, and establish asymptotic results for our estimators. We use our results to conduct large-sample inference for our measures, and we propose a computationally efficient partial bootstrap procedure to potentially improve finite-sample inference. We assess the properties of our proposed methods using numerical studies, and we illustrate our methods with an analysis of data for predicting wine quality from its physicochemical properties. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.29916753.v1
title: Nonparametric Assessment of Variable Selection and Ranking Algorithms

description: Selecting from or ranking a set of candidate variables in terms of their capacity for predicting an outcome of interest is an important task in many scientific fields. A variety of methods for variable selection and ranking have been proposed in the literature. In practice, it can be challenging to know which method is most appropriate for a given dataset. In this article, we propose methods of comparing variable selection and ranking algorithms. We first introduce measures of the quality of variable selection and ranking algorithms. We then define estimators of our proposed measures, and establish asymptotic results for our estimators. We use our results to conduct large-sample inference for our measures, and we propose a computationally efficient partial bootstrap procedure to potentially improve finite-sample inference. We assess the properties of our proposed methods using numerical studies, and we illustrate our methods with an analysis of data for predicting wine quality from its physicochemical properties. Supplementary materials for this article are available online.
DOI: 10.15468/dl.txrjqh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Erigeron glaucus)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014925-251009101135966/datasets/export for details.
DOI: 10.5281/zenodo.17053917
title: Hydrophysical data collected with SeaExplorer glider in South-Western Black Sea, July 2024

description: The dataset contains hydrophysical data collected in South-Western Black Sea withing the Turkish EEZ in July 2024 in mission supported by EU-funded BRIDGE-BS project.



The data were acquired with underwater glider SeaExplorer X2 of ALSEAMAR equipped with the following instruments: 1) RBRlegato³ C.T.D (non-pumped flow) with temperature, conductivity and pressure sensors; 2) JFE Advantech Co. Rinko Fast Optical DO sensor; 3) Wet Labs ECO Puck (fluorescence and turbidity); 4) Sea-Bird Scientific Deep SUNA Ocean Nitrate Sensor; 5) Altimeter. Raw data files from the mission were combined and saved in one Excel file.
DOI: 10.5281/zenodo.17053918
title: Hydrophysical data collected with SeaExplorer glider in South-Western Black Sea, July 2024

description: The dataset contains hydrophysical data collected in South-Western Black Sea withing the Turkish EEZ in July 2024 in mission supported by EU-funded BRIDGE-BS project.



The data were acquired with underwater glider SeaExplorer X2 of ALSEAMAR equipped with the following instruments: 1) RBRlegato³ C.T.D (non-pumped flow) with temperature, conductivity and pressure sensors; 2) JFE Advantech Co. Rinko Fast Optical DO sensor; 3) Wet Labs ECO Puck (fluorescence and turbidity); 4) Sea-Bird Scientific Deep SUNA Ocean Nitrate Sensor; 5) Altimeter. Raw data files from the mission were combined and saved in one Excel file.
DOI: 10.15468/dl.eshdwv
title: Occurrence Download

description: A dataset containing 7928 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Nasua narica"
 ]
}

 The dataset includes 7928 records from 95 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014927-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.87uvxt
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Solenogastres)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((150 10,160 10,160 20,150 20,150 10))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014928-251009101135966/datasets/export for details.
DOI: 10.15468/dl.mws4wb
title: Occurrence Download

description: A dataset containing 14311 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Rhamnus lycioides L.",
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 14311 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014926-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17053168
title: Hydrophysical data collected with ROTV ScanFish in South-Western Black Sea, July 2024

description: The dataset contains hydrophysical data collected in South-Western Black Sea withing the Turkish EEZ in July 2024 during the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project.



The data were acquired with ROTV ScanFish of EIVA equipped with AML CPT and AML SD sensors, Optode 4330F sensor, and WETLabs FLNTU sensor. Towing was done on speed ~3.5 knots. Raw data from sensors were averaged within 1 sec intervals and converted to ODV format. The output file contains following parameters: Pressure, Salinity, Density, Conductivity, Temp AML, O2Concentration, AirSaturation [%], Temp Optode, ECOFLNTU Chla, and ECOFLNTU Turbidity.
DOI: 10.5281/zenodo.17053167
title: Hydrophysical data collected with ROTV ScanFish in South-Western Black Sea, July 2024

description: The dataset contains hydrophysical data collected in South-Western Black Sea withing the Turkish EEZ in July 2024 during the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project.



The data were acquired with ROTV ScanFish of EIVA equipped with AML CPT and AML SD sensors, Optode 4330F sensor, and WETLabs FLNTU sensor. Towing was done on speed ~3.5 knots. Raw data from sensors were averaged within 1 sec intervals and converted to ODV format. The output file contains following parameters: Pressure, Salinity, Density, Conductivity, Temp AML, O2Concentration, AirSaturation [%], Temp Optode, ECOFLNTU Chla, and ECOFLNTU Turbidity.
DOI: 10.15468/dl.ab9zq8
title: Occurrence Download

description: A dataset containing 205 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cephalopoda)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((120 -10,130 -10,130 0,120 0,120 -10))"
 ]
}

 The dataset includes 205 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014929-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17053094
title: Hydrophysical data collected with ROTV ScanFish in Black Sea, June 2023

description: The dataset contains hydrophysical data collected in Black Sea withing the Turkish EEZ in Jun 2023 during the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project.



The data were acquired with ROTV ScanFish of EIVA equipped with AML CPT and AML SD sensors, Optode 4330F sensor, and WETLabs FLNTU sensor. Towing was done on speed ~3.5 knots. Raw data from sensors were averaged within 1 sec intervals and converted to ODV format. The output file contains following parameters: Pressure, Salinity, Density, Conductivity, Temp AML, O2Concentration, AirSaturation [%], Temp Optode, ECOFLNTU Chla, and ECOFLNTU Turbidity.
DOI: 10.5281/zenodo.17053093
title: Hydrophysical data collected with ROTV ScanFish in Black Sea, June 2023

description: The dataset contains hydrophysical data collected in Black Sea withing the Turkish EEZ in Jun 2023 during the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project.



The data were acquired with ROTV ScanFish of EIVA equipped with AML CPT and AML SD sensors, Optode 4330F sensor, and WETLabs FLNTU sensor. Towing was done on speed ~3.5 knots. Raw data from sensors were averaged within 1 sec intervals and converted to ODV format. The output file contains following parameters: Pressure, Salinity, Density, Conductivity, Temp AML, O2Concentration, AirSaturation [%], Temp Optode, ECOFLNTU Chla, and ECOFLNTU Turbidity.
DOI: 10.15468/dl.54hars
title: Occurrence Download

description: A dataset containing 580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cephalopoda)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((130 -10,140 -10,140 0,130 0,130 -10))"
 ]
}

 The dataset includes 580 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014930-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.