cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/ww0z-7373
title: model 3.7

description: test
DOI: 10.21227/cr0j-g039
title: model 3.8

description: test
DOI: 10.25318/1310078801-fra
title: Problèmes de santé chroniques chez les aînés de 65 ans et plus, Enquête canadienne sur la santé des aînés

description: Problèmes de santé chroniques chez les aînés de 65 ans et plus, Enquête canadienne sur la santé des aînés, par groupe d'âge et sexe, Canada (excluant les territoires) et provinces.
DOI: 10.25318/1310078901-eng
title: Health characteristics of seniors aged 65 and over, Canadian Health Survey on Seniors

description: Health characteristics of seniors aged 65 and over, Canadian Health Survey on Seniors, by age group and sex, Canada (excluding territories) and provinces.
DOI: 10.6073/pasta/17a064489cff7e8eb43c3db5d3df5938
title: Reactive oxygen species alter chemical composition and adsorptive fractionation of soil-derived organic matter

description: This is the data archive for the corresponding publication with the same title (doi: 10.1016/j.geoderma.2020.114805). Reactive oxygen species (ROS), formed during redox fluctuations in iron-rich soils, have been known to stimulate lignin degradation, although not much is known about how they alter soil organic matter (SOM) composition and interaction with mineral surfaces. We conducted a laboratory experiment to see how ROS altered SOM composition and adsorptive fractionation onto Fe-mineral surfaces. We reacted water extracts of SOM with ·OH, produced by the Fenton reaction, and then conducted a sorption experiment of the extracts with goethite to analyze the amount and quality of SOM adsorbed. The Fenton reaction preferentially consumed low-O, mostly aromatic molecules, and new high-O molecules were detected post-Fenton, nearly half of which were carbohydrate-like. Although the amount of C adsorbed did not change after oxidation, the post-Fenton adsorbed molecules were more oxidized. Pre-Fenton adsorption was dominated by aromatic molecules (90%), but post-Fenton, the adsorbed molecules were 75% aromatic and 25% carbohydrate-like. We show that the ·OH radical oxidized SOM and shifted patterns of adsorption to a more oxidized pool. Because adsorption to minerals is thought to stabilize SOM, our results suggest that ROS may alter the availability and stabilization patterns of SOM
DOI: 10.25318/1310078901-fra
title: Caractéristiques de santé des aînés de 65 ans et plus, Enquête canadienne sur la santé des aînés

description: Caractéristiques de santé des aînés de 65 ans et plus, Enquête canadienne sur la santé des aînés, par groupe d'âge et sexe, Canada (excluant les territoires) et provinces.
DOI: 10.5066/f7c24tks
title: Data file containing the raw responses to an online sedimentation survey from 49 National Wildlife Refuges in U.S. Fish and Wildlife Service Region 3 (an area encompassing the states of Illinois, Indiana, Iowa, Ohio, Michigan, Minnesota, Missouri, and Wisconsin) and Region 6 (an area encompassing the states of Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming).

description: Data file containing the raw responses to an online sedimentation survey from 49 National Wildlife Refuges in U.S. Fish and Wildlife Service Region 3 (an area encompassing the states of Illinois, Indiana, Iowa, Ohio, Michigan, Minnesota, Missouri, and Wisconsin) and Region 6 (an area encompassing the states of Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming). The survey was issued in the spring of 2014. This file contains responses to only those questions that were listed as being dichotomous (e.g., yes or no) or multiple choice in order to protect the identities of the respondents.
DOI: 10.6084/m9.figshare.13180172
title: R0220_20180302a_videos

description: Rat 0220, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.21227/3cxf-jb88
title: model 3.7

description: test
DOI: 10.6084/m9.figshare.12743939.v1
title: Data from "Obstacles to the Reuse of Study Metadata in ClinicalTrials.gov"

description: This fileset provides supporting data and corpora for the empirical study described in: <br><b>Laura Miron, Rafael S. Goncalves and Mark A. Musen. Obstacles to the Reuse of Metadata in ClinicalTrials.gov</b><br><i>Description of files</i><br><b>Original data files:</b>- AllPublicXml.zip contains the set of all public XML records in ClinicalTrials.gov (protocols and summary results information), on which all remaining analyses are based. Set contains 302,091 records downloaded on April 3, 2019.- public.xsd is the XML schema downloaded from ClinicalTrials.gov on April 3, 2019, used to validate records in AllPublicXML.<br><b>BioPortal API Query Results</b>- condition_matches.csv contains the results of querying the BioPortal API for all ontology terms that are an 'exact match' to each condition string scraped from the ClinicalTrials.gov XML. Columns={filename, condition, url, bioportal term, cuis, tuis}. - intervention_matches.csv contains BioPortal API query results for all interventions scraped from the ClinicalTrials.gov XML. Columns={filename, intervention, url, bioportal term, cuis, tuis}.<br><br><b>Analytical Results:</b>- EC_human_review.csv contains the results of a manual review of random sample eligibility criteria from 400 CT.gov records. Table gives filename, criteria, and whether manual review determined the criteria to contain criteria for "multiple subgroups" of participants.- completeness.xlsx contains counts and percentages of interventional records missing fields required by FDAAA801 and its Final Rule.- industry_completeness.xlsx contains percentages of interventional records missing required fields, broken up by agency class of trial's lead sponsor ("NIH", "US Fed", "Industry", or "Other"), and before and after the effective date of the Final Rule- location_completeness.xlsx contains percentages of interventional records missing required fields, broken up by whether record listed at least one location in the United States and records with only international location (excluding trials with no listed location), and before and after the effective date of the Final Rule<br>
DOI: 10.6084/m9.figshare.13180193
title: R0220_20180303a_videos

description: Rat 0220, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13180193.v1
title: R0220_20180303a_videos

description: Rat 0220, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.5066/f7j964d0
title: Harmonization of Forest Disturbance Datasets of the Conterminous United States from 1986-2011

description: A wide range of spatial forest disturbance datasets exist for the conterminous United States, yet inconsistencies between map products arise because of differing programmatic objectives and methodologies. Researchers harmonized maps from multiple data sources (i.e., Global Forest Change, Landfire Vegetation Disturbance, National Land Cover Database, Vegetation Change Tracker, Web-enabled Landsat Data, and Monitoring Trends in Burn Severity) using a pixel-based data fusion process. The harmonization process, which involves fitting common class ontologies and testing spatial congruency, reconciled differences in forest harvest/other and forest fire across four intervals (1986-1992, 1992-2001, 2001-2006, and 2006-2011) by relying on convergence of evidence across all datasets available for each interval. Pixels with high agreement across datasets were retained and pixels mapped by only one dataset were deleted. Results indicate that harmonization of readily-available data increases data utility by incorporating causality information across input datasets, extending the monitoring period, and improving user�s accuracies. However, conservative rules for flagging disturbance contribute to lower producer�s accuracies relative to the best available stand-alone maps. Omission errors remain high for all forest disturbance maps due to underlying limitations in Landsat classification algorithms.
DOI: 10.5281/zenodo.4243020
title: Alligator Reef Fishes species checklist 2020.xlsx Spreadsheet of the checklist of fish species documented in the study area of Alligator Reef & environs, Florida Keys, USA, by Starck, Estapé & Estapé (2017), updated with 14 additional species records

description: <em>Alligator Reef Fishes species checklist 2020.xlsx</em> Spreadsheet of the checklist of fish species documented in the study area of Alligator Reef & environs, Florida Keys, USA, by Starck, Estapé & Estapé (2017), updated with 14 additional species records
DOI: 10.5281/zenodo.4243019
title: Alligator Reef Fishes species checklist 2020.xlsx Spreadsheet of the checklist of fish species documented in the study area of Alligator Reef & environs, Florida Keys, USA, by Starck, Estapé & Estapé (2017), updated with 14 additional species records

description: <em>Alligator Reef Fishes species checklist 2020.xlsx</em> Spreadsheet of the checklist of fish species documented in the study area of Alligator Reef & environs, Florida Keys, USA, by Starck, Estapé & Estapé (2017), updated with 14 additional species records
DOI: 10.5066/p9vdbfwj
title: Data Release of Capacity and Area of Grand Lake O' the Cherokees, Northeastern Oklahoma, 2009

description: The U.S. Geological Survey, in cooperation with the Grand River Dam Authority, computed a 2009 capacity and area table of Grand Lake O' the Cherokees. The capacity and area table defines the relation between the elevation of the water surface and the volume and area of water that is impounded. The capacity and area of Grand Lake O' the Cherokees were computed from a Triangular Irregular Network (TIN) surface created in Esri ArcGIS 10.5.1, a geographic information system (GIS). The TIN surface was created from three datasets: (1) a 2009 Oklahoma Water Resources Board (OWRB) bathymetric survey of Grand Lake (OWRB, 2009, 2016), (2) a 2017 USGS bathymetric survey of the Neosho, Spring, and Elk Rivers (Hunter and others, 2017; Smith and others, 2017), and (3) a 2010 lidar-derived digital elevation model (DEM) (USGS, 2016a). Where the USGS and OWRB survey data overlapped, the more recently collected USGS data were given preference. The DEM data were used in areas with land-surface elevations above the conservation pool elevation of 743.40 ft above NAVD88. Because the OWRB (2009) bathymetric survey data were the predominant source of data used (in terms of quantity and areal coverage), the results and products of this data release and the report (Hunter and Labriola, 2019) were considered to reflect bathymetric conditions in 2009.
DOI: 10.5066/f72805sc
title: Bathymetry and capacity of Shawnee Reservoir, Oklahoma, 2016

description: The U.S. Geological Survey (USGS), in cooperation with the City of Shawnee, performed a detailed bathymetric survey of Shawnee Reservoir in 2016. Shawnee Reservoir (locally known as Shawnee Twin Lakes) is a manmade reservoir on South Deer Creek in Pottawatomie County, Oklahoma. The reservoir consists of two lakes connected by an equilibrium channel. The southern lake (Shawnee City Lake Number 1) was created in 1935 and the northern lake (Shawnee City Lake Number 2) was created in 1960. Shawnee Reservoir has a normal pool elevation of 1,069.0 feet above the North American Vertical Datum of 1988 (NAVD 88). The auxiliary spillway, which defines the flood pool, is at an elevation of 1,075.0 feet above NAVD 88.
DOI: 10.5281/zenodo.4243039
title: Estadísticas de jugadores ACB

description: Dataset que contiene los datos individuales de todos los jugadores que juegan en la ACB actualmente. Los datos incluidos corresponden a las estadísticas recogidas durante todas las temporadas en las que los jugadores han jugado en esta liga.
DOI: 10.5281/zenodo.4243038
title: Estadísticas de jugadores ACB

description: Dataset que contiene los datos individuales de todos los jugadores que juegan en la ACB actualmente. Los datos incluidos corresponden a las estadísticas recogidas durante todas las temporadas en las que los jugadores han jugado en esta liga.
DOI: 10.6084/m9.figshare.13180196
title: R0220_20180305a_videos

description: Rat 0220, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13180196.v1
title: R0220_20180305a_videos

description: Rat 0220, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.5281/zenodo.4174236
title: Valoración acciones del Ibex35 e histórico

description: Estos datasets recogen las cotizaciones del Ibex 35 y el históricos asociado a las mismas druantes el último año.
DOI: 10.5281/zenodo.4174235
title: Valoración acciones del Ibex35 e histórico

description: Estos datasets recogen las cotizaciones del Ibex 35 y el históricos asociado a las mismas druantes el último año.
DOI: 10.5517/ccdc.csd.cc25wkwj
title: CCDC 2022498: Experimental Crystal Structure Determination

description: Related Article: Darren M. C. Ould, Jamie L. Carden, Rowan Page, Rebecca L. Melen|2020|Inorg.Chem.|59|14891|doi:10.1021/acs.inorgchem.0c01076
DOI: 10.5517/ccdc.csd.cc25wtyv
title: CCDC 2022748: Experimental Crystal Structure Determination

description: Related Article: Madeleine A. Ehweiner, Fabian Wiedemaier, Ferdinand Belaj, Nadia C. Mösch-Zanetti|2020|Inorg.Chem.|59|14577|doi:10.1021/acs.inorgchem.0c02412
DOI: 10.5517/ccdc.csd.cc25xtrp
title: CCDC 2023703: Experimental Crystal Structure Determination

description: Related Article: Li-Cheng Song, Wei Chen, Liang Zhu, Fu-Qiang Hu, Kai-Yu Jiang|2020|New J.Chem.|44|18496|doi:10.1039/D0NJ04194G
DOI: 10.5517/ccdc.csd.cc25xtsq
title: CCDC 2023704: Experimental Crystal Structure Determination

description: Related Article: Li-Cheng Song, Wei Chen, Liang Zhu, Fu-Qiang Hu, Kai-Yu Jiang|2020|New J.Chem.|44|18496|doi:10.1039/D0NJ04194G
DOI: 10.5517/ccdc.csd.cc257lst
title: CCDC 2003306: Experimental Crystal Structure Determination

description: Related Article: Anshu Singh, Ankur Maji, Aurobinda Mohanty, Kaushik Ghosh|2020|New J.Chem.|44|18399|doi:10.1039/D0NJ03081C
DOI: 10.5517/ccdc.csd.cc257ltv
title: CCDC 2003307: Experimental Crystal Structure Determination

description: Related Article: Anshu Singh, Ankur Maji, Aurobinda Mohanty, Kaushik Ghosh|2020|New J.Chem.|44|18399|doi:10.1039/D0NJ03081C
DOI: 10.5517/ccdc.csd.cc257lrs
title: CCDC 2003305: Experimental Crystal Structure Determination

description: Related Article: Anshu Singh, Ankur Maji, Aurobinda Mohanty, Kaushik Ghosh|2020|New J.Chem.|44|18399|doi:10.1039/D0NJ03081C
DOI: 10.5517/ccdc.csd.cc251cp9
title: CCDC 1997320: Experimental Crystal Structure Determination

description: Related Article: Sabrina Schwarzbich, Claudia Horstmann née Gruschka, Jasmin Simon, Lena Siebe, Alexander Moreth, Christiane Wiegand, Antonina Lavrentieva, Thomas Scheper, Anja Stammler, Hartmut Bögge, Gabriele Fischer von Mollard, Thorsten Glaser|2020|Inorg.Chem.|59|14464|doi:10.1021/acs.inorgchem.0c02255
DOI: 10.5517/ccdc.csd.cc251cn8
title: CCDC 1997319: Experimental Crystal Structure Determination

description: Related Article: Sabrina Schwarzbich, Claudia Horstmann née Gruschka, Jasmin Simon, Lena Siebe, Alexander Moreth, Christiane Wiegand, Antonina Lavrentieva, Thomas Scheper, Anja Stammler, Hartmut Bögge, Gabriele Fischer von Mollard, Thorsten Glaser|2020|Inorg.Chem.|59|14464|doi:10.1021/acs.inorgchem.0c02255
DOI: 10.5517/ccdc.csd.cc25l7lm
title: CCDC 2013530: Experimental Crystal Structure Determination

description: Related Article: Meng Sun, Kai-Yao Wang, Dong Ding, Jia-Ying Zhu, Yi-Ming Zhao, Lin Cheng, Cheng Wang|2020|Inorg.Chem.|59|13822|doi:10.1021/acs.inorgchem.0c02113
DOI: 10.5517/ccdc.csd.cc258xds
title: CCDC 2004565: Experimental Crystal Structure Determination

description: Related Article: Aleksandra Ziółkowska, Natalia Szynkiewicz, Jerzy Pikies, Łukasz Ponikiewski|2020|Dalton Trans.|49|13635|doi:10.1039/D0DT02728F
DOI: 10.5517/ccdc.csd.cc258xgv
title: CCDC 2004567: Experimental Crystal Structure Determination

description: Related Article: Aleksandra Ziółkowska, Natalia Szynkiewicz, Jerzy Pikies, Łukasz Ponikiewski|2020|Dalton Trans.|49|13635|doi:10.1039/D0DT02728F
DOI: 10.5517/ccdc.csd.cc258xbq
title: CCDC 2004563: Experimental Crystal Structure Determination

description: Related Article: Aleksandra Ziółkowska, Natalia Szynkiewicz, Jerzy Pikies, Łukasz Ponikiewski|2020|Dalton Trans.|49|13635|doi:10.1039/D0DT02728F
DOI: 10.5517/ccdc.csd.cc258xcr
title: CCDC 2004564: Experimental Crystal Structure Determination

description: Related Article: Aleksandra Ziółkowska, Natalia Szynkiewicz, Jerzy Pikies, Łukasz Ponikiewski|2020|Dalton Trans.|49|13635|doi:10.1039/D0DT02728F
DOI: 10.5517/ccdc.csd.cc258xft
title: CCDC 2004566: Experimental Crystal Structure Determination

description: Related Article: Aleksandra Ziółkowska, Natalia Szynkiewicz, Jerzy Pikies, Łukasz Ponikiewski|2020|Dalton Trans.|49|13635|doi:10.1039/D0DT02728F
DOI: 10.5517/ccdc.csd.cc258xhw
title: CCDC 2004568: Experimental Crystal Structure Determination

description: Related Article: Aleksandra Ziółkowska, Natalia Szynkiewicz, Jerzy Pikies, Łukasz Ponikiewski|2020|Dalton Trans.|49|13635|doi:10.1039/D0DT02728F
DOI: 10.5517/ccdc.csd.cc23y8bp
title: CCDC 1964542: Experimental Crystal Structure Determination

description: Related Article: Yen-Chung Huang, Wan-Yu Lan, Wei-Min Ching, Sodio C. N. Hsu|2020|New J.Chem.|44|18242|doi:10.1039/D0NJ03967E
DOI: 10.5517/ccdc.csd.cc23y8cq
title: CCDC 1964543: Experimental Crystal Structure Determination

description: Related Article: Yen-Chung Huang, Wan-Yu Lan, Wei-Min Ching, Sodio C. N. Hsu|2020|New J.Chem.|44|18242|doi:10.1039/D0NJ03967E
DOI: 10.6084/m9.figshare.13180172.v1
title: R0220_20180302a_videos

description: Rat 0220, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13185008.v1
title: Supplementary_Tables_.xlsx

description: This excel files contains:<b>Table S1.</b> Detailed absolute ages, confidence intervals and rates for the orchid family as inferred under a strict molecular clock and a birth-death model. <b>Table S2.</b> Detailed absolute ages, confidence intervals and rates for the orchid family as inferred under a relaxed molecular clock and a birth-death model. The table contains 528 rows and 16 columns<b>Table S3.</b> Phylogenetic informativeness per-site.<b>Table S4.</b> Phylogenetic net informativeness.<b>Table S5. </b>Voucher information and proportion of missing data in gene alignments.<b></b>
DOI: 10.6084/m9.figshare.13185008
title: Supplementary_Tables_.xlsx

description: This excel files contains:<b>Table S1.</b> Detailed absolute ages, confidence intervals and rates for the orchid family as inferred under a strict molecular clock and a birth-death model. <b>Table S2.</b> Detailed absolute ages, confidence intervals and rates for the orchid family as inferred under a relaxed molecular clock and a birth-death model. The table contains 528 rows and 16 columns<b>Table S3.</b> Phylogenetic informativeness per-site.<b>Table S4.</b> Phylogenetic net informativeness.<b>Table S5. </b>Voucher information and proportion of missing data in gene alignments.<b></b>
DOI: 10.5281/zenodo.4243049
title: EMUE-RMG-2-Pressure drop measurement

description: Pressure Drop Measurement This example demonstrates how correlations can sometimes be removed from an uncertainty evaluation by modifying the measurement equation so that strongly correlated quantity estimates do not appear together. This is demonstrated by an example considering the pressure drop in a pressurised vessel, in which the effect of correlation between temperature measurements is removed. In this example the uncertainty associated with an estimate of pressure drop is appreciably smaller when correlation is taken into consideration. Files contained in dataset are: EMUE-RMG- Pressure drop measurement – UKAS.pdf, EMPIR.jpg- figure file, EMUELogo-03.jpg- figure file, Example_A.tex: LaTeX file to be compiled in order to produce EMUE-RMG- Pressure drop measurement – UKAS.pdf, MCMandGUMnewWithCorr.jpg: figure file, MCMandGUMnewWithoutCor.jpg: figure file, reference.bib: bibliography file, Compendium.bib: bibliography file, GUM_WithCorrelations.mat /GUM_WithoutCorrelations.mat: MATLAB function that calculates measurement uncertainty by following the GUM principle (with or without correlations), GUMSupp1_WithCorrelations.mat /GUMSupp1_WithoutCorrelations.mat: MATLAB function that calculates measurement uncertainty by following GUM Supplement 1 principle (with or without correlations), InputData_WithCorrelations.mat /InputData_WithoutCorrelations.mat: MATLAB function for input data (with or without correlations), PlotGUM_WithCorrelations.mat /PlotGUM_WithoutCorrelations.mat: MATLAB function for plotting the results (with or without correlations), PlotGUMAndMCM_WithCorrelations.mat /PlotGUMAndMCM_WithoutCorrelations.mat: MATLAB function for plotting the results (with or without correlations), Results_WithCorrelations.mat /Results_WithoutCorrelations.mat: MATLAB function for displaying the results (with or without correlations), SetFormattingSymbols_WithCorrelations.mat /SetFormattingSymbols_WithoutCorrelations.mat: MATLAB function for setting formatting symbols, UKASPressureDropExample_WithCorrelations.mat /UKASPressureDropExample_WithoutCorrelations.mat: Model developed in MATLAB that calculates estimated pressure drop and the associated measurement uncertainty (GUM and Monte Carlo method). One file calculates the uncertainties with and the other without correlations. These files use MATLAB functions (developed for this example) that are listed above: SetFormattingSymbols, InputData, GUM, GUMSupp1, Results, PlotGUMAndMCM, PlotGUM.
description: It should be noticed that there are two types of .mat files: "WithoutCorrelations" and "WithCorrelations". When running the program, the program UKASPressureDropExample_WithoutCorrelations will use MATLAB functions that have "WithoutCorrelations" in their name. The other will use only functions that have WithCorrelations in their name. However, when running the program it is necessary to ensure that all the functions that are used and the main script (UKASPressureDropExample.mat) are located in one folder.