cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22822037.v2
title: Independence Weights for Causal Inference with Continuous Treatments

description: Studying causal effects of continuous treatments is important for gaining a deeper understanding of many interventions, policies, or medications, yet researchers are often left with observational studies for doing so. In the observational setting, confounding is a barrier to the estimation of causal effects. Weighting approaches seek to control for confounding by reweighting samples so that confounders are comparable across different treatment values. Yet, for continuous treatments, weighting methods are highly sensitive to model misspecification. In this article we elucidate the key property that makes weights effective in estimating causal quantities involving continuous treatments. We show that to eliminate confounding, weights should make treatment and confounders independent on the weighted scale. We develop a measure that characterizes the degree to which a set of weights induces such independence. Further, we propose a new model-free method for weight estimation by optimizing our measure. We study the theoretical properties of our measure and our weights, and prove that our weights can explicitly mitigate treatment-confounder dependence. The empirical effectiveness of our approach is demonstrated in a suite of challenging numerical experiments, where we find that our weights are quite robust and work well under a broad range of settings. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.22822037.v1
title: Independence weights for causal inference with continuous treatments

description: Studying causal effects of continuous treatments is important for gaining a deeper understanding of many interventions, policies, or medications, yet researchers are often left with observational studies for doing so. In the observational setting, confounding is a barrier to the estimation of causal effects. Weighting approaches seek to control for confounding by reweighting samples so that confounders are comparable across different treatment values. Yet, for continuous treatments, weighting methods are highly sensitive to model misspecification. In this paper we elucidate the key property that makes weights effective in estimating causal quantities involving continuous treatments. We show that to eliminate confounding, weights should make treatment and confounders independent on the weighted scale. We develop a measure that characterizes the degree to which a set of weights induces such independence. Further, we propose a new model-free method for weight estimation by optimizing our measure. We study the theoretical properties of our measure and our weights, and prove that our weights can explicitly mitigate treatment-confounder dependence. The empirical effectiveness of our approach is demonstrated in a suite of challenging numerical experiments, where we find that our weights are quite robust and work well under a broad range of settings.
DOI: 10.34740/kaggle/dsv/6248189
title: COVID Vaccination in World (updated daily)
DOI: 10.25392/leicester.data.23829570
title: Efficient Word Segmentation is Preserved in Older Adult Readers: Evidence from Eye Movements during Chinese Reading.

description: These data flles are for two eye movement experiments investigating the process of word segmentation for young and older adult Chinese readers.
DOI: 10.25392/leicester.data.23829570.v1
title: Efficient Word Segmentation is Preserved in Older Adult Readers: Evidence from Eye Movements during Chinese Reading.

description: These data flles are for two eye movement experiments investigating the process of word segmentation for young and older adult Chinese readers.
DOI: 10.48510/fk2/6zrduy/5e3t2h
title: Data_DN_PN_survey_2012_2013_lv.tab

description: :unav
DOI: 10.48510/fk2/6zrduy/tdtehn
title: questionnaire_DN_PN_survey_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/6zrduy/0tbpvy
title: Methodology_employees_survey_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/6zrduy/xrdm28
title: Data_DN_PN_survey_2012_2013.csv

description: :unav
DOI: 10.48510/fk2/6zrduy
title: Working Conditions and Risks in Latvia 2012 - 2013: Survey of Employees and Self-Employed

description: The Work conditions and risks in Latvia national surveys were conducted in Latvia in 2006, 2010, 2013, 2018 and 2022. The aim of these surveys is to gather evidence on situations related to occupational risk factors, occupational health, safety and to analyze the dynamics of the data obtained and identify the causes of the existing problems. This data serves as a basis to develop proposals for improving the practical implementation of the legal framework and foundation for effective decision making. A more detailed description of the methods is available in the methodology file.
DOI: 10.26050/wdcc/ar6.c6spinic8
title: IPCC DDC: INM INM-CM4-8 model output prepared for CMIP6 ScenarioMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.INM.INM-CM4-8' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The INM-CM4-8 climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM4-8 (2x1.5; 180 x 120 longitude/latitude; 21 levels; top level sigma = 0.01), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E; 360 x 318 longitude/latitude; 40 levels; sigma vertical coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6spinic0
title: IPCC DDC: INM INM-CM5-0 model output prepared for CMIP6 ScenarioMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.INM.INM-CM5-0' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The INM-CM5-0 climate model, released in 2016, includes the following components: aerosol: INM-AER1, atmos: INM-AM5-0 (2x1.5; 180 x 120 longitude/latitude; 73 levels; top level sigma = 0.0002), land: INM-LND1, ocean: INM-OM5 (North Pole shifted to 60N, 90E. 0.5x0.25; 720 x 720 longitude/latitude; 40 levels; vertical sigma coordinate), seaIce: INM-ICE1. The model was run by the Institute for Numerical Mathematics, Russian Academy of Science, Moscow 119991, Russia (INM) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 50 km, seaIce: 50 km.
DOI: 10.24378/exe.4726
title: Does Brexit overcome the globalisation trilemma? How British business assess the trade relationship with the EU (dataset)

description: This is the dataset used for the Kroger & Dede (2023) article "Does Brexit overcome the globalisation trilemma? How British business assess the trade relationship with the EU" published in British Politics.
description: The article associated with this dataset is available in ORE at: http://hdl.handle.net/10871/133707
DOI: 10.48510/fk2/lhxysn/lh8luf
title: Methodology_employees_survey_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/lhxysn/hqg16l
title: Data_DN_survey_2019_2021_lv.tab

description: :unav
DOI: 10.48510/fk2/lhxysn/mqmuyz
title: Data_DN_survey_2019_2021.csv

description: :unav
DOI: 10.48510/fk2/lhxysn/tccpaa
title: questionnaire_DN_survey_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/lhxysn
title: Working Conditions and Risks in Latvia 2019 - 2021: Survey of Employees

description: The Work conditions and risks in Latvia national surveys were conducted in Latvia in 2006, 2010, 2013, 2018 and 2022. The aim of these surveys is to gather evidence on situations related to occupational risk factors, occupational health, safety and to analyze the dynamics of the data obtained and identify the causes of the existing problems. This data serves as a basis to develop proposals for improving the practical implementation of the legal framework and foundation for effective decision making. A more detailed description of the methods is available in the methodology file.
DOI: 10.5281/zenodo.8212716
title: Combined P-V-T Data for hcp-Fe with Reevaluated Pressures and Pressure Uncertainties

description: This dataset consists of unit-cell volumes, temperatures, and reevaluated pressures, and their related uncertainties for <em>hcp-</em>Fe. The volumes and temperatures are taken from previous studies (indicated under the column "Original Publication"), and the pressures were reevaluated using the internally consistent pressure scales of Fei <em>et al</em>., 2007. The pressure uncertainties presented here propagate uncertainties in the volume and temperature measurements, as well as the uncertainty and covariance in the equation of state parameters used to determine the pressure. Also listed are the beamline the data were originally collected at, and the compression technique (DAC= Diamond Anvil Cell; MAP= Multi-Anvil Press).
DOI: 10.5281/zenodo.8212715
title: Combined P-V-T Data for hcp-Fe with Reevaluated Pressures and Pressure Uncertainties

description: This dataset consists of unit-cell volumes, temperatures, and reevaluated pressures, and their related uncertainties for <em>hcp-</em>Fe. The volumes and temperatures are taken from previous studies (indicated under the column "Original Publication"), and the pressures were reevaluated using the internally consistent pressure scales of Fei <em>et al</em>., 2007. The pressure uncertainties presented here propagate uncertainties in the volume and temperature measurements, as well as the uncertainty and covariance in the equation of state parameters used to determine the pressure. Also listed are the beamline the data were originally collected at, and the compression technique (DAC= Diamond Anvil Cell; MAP= Multi-Anvil Press).
DOI: 10.48366/r604254
title: A Catalog of MosaicML's MPT series Large Language Models

description: Thus far the MPT model series from MosaicML, i.e. MPT-7B and MPT-30B, have proven to be very competitive with MPT-7B surpassing GPT-3 in many academic tasks, and MPT-30B surpassing perfomances by Llama-1, Falcon-40B, and all prior models from EleutherAI. This comparison showcases MosaicML's models released so far in terms of their salient properties. Increasingly with stronger models released for research, the open-sourced development of LLMs offers a promising future trajectory.
DOI: 10.5281/zenodo.7798365
title: Dataset: Periodic variation of mesoscale ultraviolet contrast at the cloud top of Venus

description: Filename:<br> mean_A_283.txt : wavelength of 283 nm<br> mean_A_365.txt : wavelengths of 365 nm Description:<br> Empirical equigonal UV albedo of Venus as a function of the phase angle determined from Akatsuki UVI data. Format (text file): <br> 1st column: Phase angle (deg)<br> 2nd column: A:Mean albedo<br> 3rd column: SD:Standard deviation Filename:<br> period1_283nm.txt : Period 1, 283 nm<br> period1_365nm.txt : Period 1, 365 nm<br> period2_283nm.txt : Period 2, 283 nm<br> period2_365nm.txt : Period 2, 365 nm Description:<br> Time series of the standard deviation of mesoscale UV contrast and the mean brightness of Venus. Format (text file):<br> 1st column: Image file name<br> 2nd column: Elapsed time (h)<br> 3rd column: Phase angle (deg)<br> 4th column: Standard deviation (W/m2/str/m)<br> 5th column: Standard deviation in AM<br> 6th column: Standard deviation in PM<br> 7th column: Mean brightness (W/m2/str/m)<br> 8th column: Mean brightness in AM<br> 9th column: Mean brightness in PM Filename:<br> uvi_20160425_131340_283_l3b_v10.nc<br> uvi_20160425_151341_283_l3b_v10.nc<br> uvi_20160425_171339_283_l3b_v10.nc<br> uvi_20160506_101341_283_l3b_v10.nc<br> uvi_20160506_121340_283_l3b_v10.nc<br> uvi_20160506_141343_283_l3b_v10.nc<br> uvi_20160517_141339_283_l3b_v10.nc<br> uvi_20160517_161339_283_l3b_v10.nc Description:<br> 2.02-micrometer mapped data taken by the IR2 camera onboard Akatsuki in Level-3 netCDF format. The data have been corrected for the point-spread function, the flat-field pattern, and the detector temperature dependence by Sato et al. (2020, Icarus, 345, 113682, https://doi.org/10.1016/j.icarus.2020.113682). Format (binary file):<br> netCDF<br> The file names indicate the year, date and time of each observation.
DOI: 10.5281/zenodo.7798366
title: Dataset: Periodic variation of mesoscale ultraviolet contrast at the cloud top of Venus

description: Filename:<br> mean_A_283.txt : wavelength of 283 nm<br> mean_A_365.txt : wavelengths of 365 nm Description:<br> Empirical equigonal UV albedo of Venus as a function of the phase angle determined from Akatsuki UVI data. Format (text file): <br> 1st column: Phase angle (deg)<br> 2nd column: A:Mean albedo<br> 3rd column: SD:Standard deviation Filename:<br> period1_283nm.txt : Period 1, 283 nm<br> period1_365nm.txt : Period 1, 365 nm<br> period2_283nm.txt : Period 2, 283 nm<br> period2_365nm.txt : Period 2, 365 nm Description:<br> Time series of the standard deviation of mesoscale UV contrast and the mean brightness of Venus. Format (text file):<br> 1st column: Image file name<br> 2nd column: Elapsed time (h)<br> 3rd column: Phase angle (deg)<br> 4th column: Standard deviation (W/m2/str/m)<br> 5th column: Standard deviation in AM<br> 6th column: Standard deviation in PM<br> 7th column: Mean brightness (W/m2/str/m)<br> 8th column: Mean brightness in AM<br> 9th column: Mean brightness in PM
DOI: 10.20387/bonares-mpsx-gk22
title: Soil and rhizosphere properties related to carbon allocation processe at Hohenschulen field site in the first trial year of Rhizo4Bio – RootWayS project.

description: In the winter half-year 2020/2021, winter cover crops were grown in 10 trial variants at the Hohenschulen trial site. The soils at the trial site are mainly stagnic Luvisols derived from glacial till. The variants were arranged in a randomized block design with four replications. In spring 2021, maize was planted on the site, and the soil of all plots was sampled in different depths at different growth stages of the maize. Soil samples were taken selectively from cover crop root channels and maize rhizosphere and analyzed for parameters related to carbon allocation and wettability.


Research domain: None

Research question: None
DOI: 10.6084/m9.figshare.23864274
title: Carini_etal_2023_LOM

description: Supporting datasets and R scripts for Carini et al. 2023.Datasets: Larval shell area measurements, larval shell elemental composition (EDX), number of split larval shells, larval shell protein IDs.R scripts: areavalvemc.R= larval shell area, splitvalvesmc.R= removal of organic structures, edxmc.R= elemental analysis.Further details regarding the datasets and scripts can be found in the readme file.
DOI: 10.6084/m9.figshare.23864274.v1
title: Carini_etal_2023_LOM

description: Supporting datasets and R scripts for Carini et al. 2023.Datasets: Larval shell area measurements, larval shell elemental composition (EDX), number of split larval shells, larval shell protein IDs.R scripts: areavalvemc.R= larval shell area, splitvalvesmc.R= removal of organic structures, edxmc.R= elemental analysis.Further details regarding the datasets and scripts can be found in the readme file.
DOI: 10.48366/r604259
title: Multi-Sensor Time-Series Multispectral Remote Sensing Data for Crop Management

description: This comparison describes a research or practical application scenario where data from different remote sensing sensors, gathered over time and capturing multiple spectral bands, is being harnessed to optimize crop management strategies. The insights gained from this comparison of multi-sensor time-series multispectral approach can lead to more informed decisions for better crop productivity and sustainable agriculture.
DOI: 10.6084/m9.figshare.23864229.v1
title: <b>Refine localizations of functional variants affecting eggshell color of Lueyang black-boned chicken in the SLCO1B3</b>

description: Genotype, relatedness matrix and eggshell color data for association analysis and data from the reporter assay.
DOI: 10.34740/kaggle/dsv/6248387
title: CIC-MalMem2022
DOI: 10.5281/zenodo.8213144
title: Monthly lake water quality data (May-September 2022) following the Greenwood Fire in northeastern Minnesota v1.0

description: This repository contains lake water quality responses to the 2021 Greenwood Fire in Superior National Forest, Minnesota, USA (near Isabella, MN in northeastern MN). Thirty lakes (15 burned watershed, 15 control) were sampled monthly from May-September 2022 along various fire disturbance gradients (e.g., % watershed burned) and in relation to hydrologic connectivity (i.e., drainage vs. isolated lakes). Much of the non-water quality data we used came from published sources, which are described and referenced below. This repository also contains R code used to analyze and visualize data, as well as some output figures.
description: A few moose were seen during sampling trips.
DOI: 10.5281/zenodo.8213143
title: Monthly lake water quality data (May-September 2022) following the Greenwood Fire in northeastern Minnesota v1.0

description: This repository contains lake water quality responses to the 2021 Greenwood Fire in Superior National Forest, Minnesota, USA (near Isabella, MN in northeastern MN). Thirty lakes (15 burned watershed, 15 control) were sampled monthly from May-September 2022 along various fire disturbance gradients (e.g., % watershed burned) and in relation to hydrologic connectivity (i.e., drainage vs. isolated lakes). Much of the non-water quality data we used came from published sources, which are described and referenced below. This repository also contains R code used to analyze and visualize data, as well as some output figures.
description: A few moose were seen during sampling trips.
DOI: 10.25318/2710037001-eng
title: Adoption of additional advanced technologies, by industry and enterprise size

description: Survey of advanced technology, adoption of additional advanced technologies, North American Industry Classification System (NAICS) and enterprise size for Canada and certain provinces, in 2022.
DOI: 10.23725/e9wn-jp22
title: NWD316606.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD316606.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/ewqm-fg72
title: NWD478052.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD478052.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/f00b-nt95
title: NWD169553.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD169553.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/f0xn-7f60
title: NWD477676.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD477676.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/fcte-wq37
title: NWD398277.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD398277.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/fhsj-zd54
title: NWD237601.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD237601.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/fpzx-k570
title: NWD237829.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD237829.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/fx3c-va15
title: NWD237997.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD237997.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/gfqh-tr15
title: NWD237653.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD237653.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/ghw8-h897
title: NWD102925.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD102925.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/gq6h-2k11
title: NWD103241.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD103241.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/jfx2-zk85
title: NWD316720.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD316720.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/k52y-e234
title: NWD477178.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD477178.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/kc1m-fn60
title: NWD103550.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD103550.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/kddj-b491
title: NWD925350.freeze5.v1.vcf.gz

description: TOPMed: NWD925350.freeze5.v1.vcf.gz <br>File: VCF file
DOI: 10.23725/kx5m-cn64
title: NWD398592.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD398592.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/mcrt-k597
title: NWD398826.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD398826.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/mwrz-zn30
title: NWD398491.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD398491.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/mxdn-np55
title: NWD103411.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD103411.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/nbk9-j970
title: NWD398261.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD398261.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/ncqe-t366
title: NWD477963.freeze5.v1.vcf.gz.csi

description: TOPMed: NWD477963.freeze5.v1.vcf.gz.csi <br>File: VCF CSI file
DOI: 10.23725/nnrx-e241
title: NWD844119.freeze5.v1.vcf.gz

description: TOPMed: NWD844119.freeze5.v1.vcf.gz <br>File: VCF file