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1,663 results for “BIAS”
Data from: Across space and time: a review of sampling and analytical biases in fossil data across macroecological scales
<p>Quantitative studies of fossil data have proven critical to a number of major macroevolutionary and macroecological discoveries, such as the 'Big 5' mass extinctions of the Phanerozoic. The development and easy accessibility of major meta-data sources such as the Paleobiology Database and Geobiodiversity Database have also spurred the widespread application of these data to testing ecological hypotheses at finer spatiotemporal and phylogenetic scales. However, issues of preservational/taphonomic biases, sampling/collecting biases, taxonomic issues, and analytical choice can impact the degree of interpretative resolution possible, and even obscure biological 'signal' from error/bias-introduced 'noise'. The degree to which these factors can impact analytical interpretations is not well-documented in comparison to the scale of use of these data sources. Here, we review the many forms of systematic error that can creep into a paleoecological study, from the stage of data collection to the interpretation of analytical results, and provide two case studies based upon re-analysis of previously-published datasets to illustrate the varying impacts of such biases. The first case study focuses on the Cambrian Burgess Shale, and the second on the Belly River Group, with both representing highly-sampled, taphonomically characterized, and spatiotemporally-constrained datasets developed through multiple years of sustained field collecting. In the former, we illustrate the impacts of collecting bias through quantitative comparisons of collected vs. discarded specimens over multiple field seasons, illustrating the impact of this data loss on ecological reconstructions and analysis. In the latter case study, we review the impact of preservational biases, the approaches to their quantification and mitigation, where these approaches have led to misinterpretations in the past, and the differences in ecological resolution that result from occurrence vs abundance approaches in macroecological analysis. Lastly, we synthesize these case studies with our review of past approaches to propose a series of recommendations for future paleoecological and macroecological studies, emphasizing the continued importance of high-quality primary data and ongoing need for a first-principles approach to address existing issues of missing data.</p>
Simulation data for "Structural biases in disordered proteins are prevalent in the cell " by Moses & Guadalupe et al. (2023)
<p>This dataset contains complete atomistic ensembles, as reported by Moses & Guadalupe et al. </p> <p><strong>Structural biases in disordered proteins are prevalent in the cell </strong><br> David Moses*, Karina Guadalupe*, Feng Yu, Eduardo Flores, Anthony Perez, Ralph McAnelly, Nora M. Shamoon, Gagandeep Kaur, Estefania Cuevas-Zepeda, Andrea D. Merg, Erik W. Martin, Alex S. Holehouse, Shahar Sukenik</p> <p>For all general inquiries regarding this work, please contact Shahar Sukenik directly. For any specific questions regarding this set of simulations, please contact Alex and Shahar. <br> </p>
Webis-News-Bias-20
<p>This is the dataset used in the paper "<a href="https://webis.de/publications.html#chen_2020b">Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity.</a>"</p> <p>The news articles are stored in json format, one news each line. For each news, there are following fields:</p> <p> - title: the title of the news<br> - content: the content of the news<br> - source: the news portal<br> - allsides_bias: the bias indicated in the allsides.com (left, center, or right)<br> - misc: other information, such as author, date, and topics<br> - adfontes_fair: the labels from adfontesmedia.com, whehter the article is fair or not (bias, neutral, or unknown)<br> - adfontes_political: the labels from adfontesmedia.com, whether the article is political bias or not (bias, neutral, or unknown)<br> - event_id: the event id. Articles with the same event have the same id</p> <p> </p>
Supporting Data for " Impacts of the North Atlantic Biases on the Upper Troposphere/Lower Stratosphere over the Extratropical North Pacific"
<p>This repository contains the supporting data (in the NetCDF format) for the following paper:</p> <p>Joshi, R. and Zhang, R., 2023, Impacts of the North Atlantic Biases on the Upper Troposphere/Lower Stratosphere over the Extratropical North Pacific, <em>npj Clim Atmos Sci. </em><a href="https://doi.org/10.1038/s41612-023-00482-4">https://doi.org/10.1038/s41612-023-00482-4</a> </p> <p>In this study, Robust Diagnostic Calculations (RDC) are conducted in a fully coupled high-resolution climate model to correct the North Atlantic ocean circulation and associated temperature biases present in the model. The same fully coupled high-resolution climate model is used to generate a present-day control simulation without correcting North Atlantic ocean circulation biases for comparison. The long-term mean difference between the control and RDC experiments (Control minus RDC) is used to assess the influence of the North Atlantic biases on winter upper troposphere/lower stratosphere vertical motion and temperature changes over the extratropical North Pacific.</p> <p><strong>Descriptions of data files:</strong></p> <p>1. Sea Surface Temperature (SST) and ocean current at 120 m depth from control and RDC experiment as shown in Fig. 1a,d.</p> <p>RDC_SST_current_120m.nc</p> <p>Control_SST_current_120m.nc</p> <p>2. Ocean temperature and current at 2500 m depth from RDC and control experiment as shown in Fig. 1b,e.</p> <p>RDC_temp_current_2500m.nc</p> <p>Control_temp_current_2500m.nc</p> <p>3. Meridional ocean velocity in the North Atlantic at section 45<sup>o</sup>N from RDC and control experiment as shown in Fig. 1c,f.</p> <p>RDC_v45N.nc</p> <p>Control_v45N.nc</p> <p>4. Difference of wintertime (JFM) mean near-surface (2-m) air temperature, meridional eddy heat flux at 925hPa, 95th percentile large-scale extreme precipitation, and total precipitation between the control and RDC experiments, as shown in Fig. 2.</p> <p>t2m_diff.nc</p> <p>VT_diff.nc</p> <p>precip95_diff.nc</p> <p>precip_diff.nc</p> <p>5. Difference of wintertime (JFM) mean geopotential height, temperature, and winds between the control and RDC experiments at different pressure levels, as shown in Fig. 3,4.</p> <p>hght_diff_spatial.nc</p> <p>temp_diff_spatial.nc</p> <p>ucomp_diff_spatial.nc </p> <p>vcomp_diff_spatial.nc </p> <p>6. Two-sided student t-test at a 5% significance level for the statistical testing of wintertime mean geopotential height difference between the control and RDC experiments shown in Fig. 3. The file is a mask with values ‘1’ and ‘0’ where ‘0’ represents the region not significant at 5% significance level.</p> <p>hght_ttest_spatial.nc</p> <p>7. Two-sided student t-test at a 5% significance level for the statistical testing of wintertime mean air temperature difference between the control and RDC experiments shown in Fig. 4. The file is a mask with values ‘1’ and ‘0’ where ‘0’ represents the region not significant at 5% significance level.</p> <p>temp_ttest_spatial.nc</p> <p>8. Zonally averaged difference of winter (JFM) zonal wind, geopotential height, and air temperature between the control and RDC experiments over the extratropical North Pacific, as shown in Fig. 5.</p> <p>ucomp_diff_lonavg.nc</p> <p>temp_diff_lonavg.nc</p> <p>hght_diff_lonavg.nc</p> <p>9. Two-sided student t-test at a 5% significance level for the statistical testing of wintertime zonally averaged mean air temperature difference between the control and RDC experiments over extratropical North Pacific shown in Fig. 5a. The file is a mask with values ‘1’ and ‘0’ where ‘0’ represents the region not significant at 5% significance level.</p> <p>temp_ttest_lonavg.nc</p> <p>10. Two-sided student t-test at a 5% significance level for the statistical testing of wintertime zonally averaged mean zonal wind difference between the control and RDC experiments over extratropical North Pacific shown in Fig. 5b. The file is a mask with values ‘1’ and ‘0’ where ‘0’ represents the region not significant at 5% significance level.</p> <p>ucomp_ttest_lonavg.nc</p> <p>11. Difference of winter (JFM) mean vertical velocity in pressure coordinates between the control and RDC experiments, as shown in Fig. 6.</p> <p>omega_diff_spatial.nc</p> <p>12. Two-sided student t-test at a 5% significance level for the statistical testing of wintertime mean vertical velocity difference between the control and RDC experiments shown in Fig. 6. The file is a mask with values ‘1’ and ‘0’ where ‘0’ represents the region not significant at 5% significance level.</p> <p>omega_ttest_spatial.nc</p> <p>13. Contribution of the mean zonal flow advection of the temperature change to the horizontal advection as shown in Fig. 7a</p> <p>horizontal_advection_contribution.nc</p> <p>14. Contribution of the vertical advection of mean potential temperature by the change in omega to the adiabatic heating as shown in Fig. 7b</p> <p>adiabatic_heating_contribution.nc</p> <p>15. Two-sided student t-test at a 5% significance level for the statistical testing of differences in Fig. 7a and Fig. 7b. The file is a mask with values ‘1’ and ‘0’ where ‘0’ represents the region not significant at a 5% significance level.</p> <p>horizontal_advection_contribution_ttest.nc</p> <p>adiabatic_heating_contribution_ttest.nc</p> <p>16. Meridionally averaged difference of winter (JFM) geopotential height and air temperature between the control and RDC experiments over the extratropical North Pacific, as shown in Fig. 9b.</p> <p>hght_diff_latavg.nc</p> <p>temp_diff_latavg.nc</p> <p>17. Two-sided student t-test at 5% significance level for the statistical testing of wintertime meridionally averaged mean air temperature difference between the control and RDC experiments over extratropical North Pacific in Fig. 9b. The file is a mask with values ‘1’ and ‘0’ where ‘0’ represents the region not significant at 5% significance level.</p> <p>temp_ttest_latavg.nc</p> <p><strong>Acknowledgments</strong></p> <p>We acknowledge using the following data sets and model codes in this study. The World Ocean Atlas 2013 (WOA13) data were downloaded from the NOAA National Centers for Environmental Information (formerly the National Oceanographic Data) https://www.nodc.noaa.gov/cgi-bin/OC5/woa13/woa13.pl. The CSIRO ATLAS of REGIONAL SEAS 2009 version (CARS2009) data (<a href="http://www.marine.csiro.au/~dunn/cars2009/">http://www.marine.csiro.au/~dunn/cars2009/</a>) were developed and provided by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Marine and Atmospheric Research and downloaded from <a href="http://www.marine.csiro.au/atlas/">http://www.marine.csiro.au/atlas/</a>. The Japanese Ocean Flux Data set with Use of Remote Sensing Observations (J-OFURO3 V168) is for the period 1988-2013 and can be downloaded from <a href="https://www.j-ofuro.com/en/dataset">https://www.j-ofuro.com/en/dataset</a>. The code of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled climate model version 2.5 (CM2.5) is publicly available at <a href="https://www.gfdl.noaa.gov/cm2-5-and-flor-quickstart/">https://www.gfdl.noaa.gov/cm2-5-and-flor-quickstart/</a>. The relevant citations for the above datasets and model code are listed in Joshi and Zhang 2023.</p>
Studies on the side effects of methylphenidate in adults diagnosed with ADHD. The risk of bias and study quality assessed with the Effective Public Health Practice Project's Quality Assessment Tool for Quantitative Studies (QATQS) was presented as the global rating for each publication (1 - strong, 2 - moderate, 3 - weak).
<p>The data set contains the analysis of adult studies on ADHD with respect on side effects of methylphenidate. </p>
Passive Bias-Free Nonreciprocal Metasurfaces Based on Thermally Nonlinear Quasi-Bound States in the Continuum
<p>This dataset contains tabulated versions of the experimental data shown in the pictures of the publication " Passive Bias-Free Nonreciprocal Metasurfaces Based on Thermally Nonlinear Quasi-Bound States in the Continuum".</p>
Iterative convergent computation may not be a useful inductive bias for residual neural networks
<p>This repository contains the code and data necessary to reproduce the results and figures in "Iterative convergent computation may not be a useful inductive bias for residual neural networks".</p>
Figure 5 in Male-biased in-water population of loggerhead turtle (Caretta caretta) in Dalyan, Turkey possible important marine turtle area in the Mediterranean
Figure 5. Comparison of BCI between female, male, and subadult individuals (The line in the boxes represents the median value, the boxes represent interquartile range between first and third quartiles).
Confirmatory Efficacy Trial of Attention Bias Modification for Depression
ClinicalTrials.gov study NCT06361095. IPD Sharing: YES. Countries: 1. Publications: 1.
The Effect of an Education Module to Reduce Weight Bias Among Healthcare Professionals in a Private Hospital Setting
ClinicalTrials.gov study NCT04741113. IPD Sharing: NO. Countries: 1. Publications: 1.
Development of Attention Bias Modification for Depression
ClinicalTrials.gov study NCT02880215. IPD Sharing: YES. Countries: 1. Publications: 2.
Attention Bias Modification Treatment (ABMT) and Cognitive-Behavioral Group Therapy (CBGT) in Social Anxiety Disorder
ClinicalTrials.gov study NCT02338453. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Nicotine and Pavlovian Bias
ClinicalTrials.gov study NCT06027723. IPD Sharing: YES. Countries: 1. Publications: 4.
Pilot Intervention for Social Biases in Eating Disorders
ClinicalTrials.gov study NCT04877158. IPD Sharing: NO. Countries: 1. Publications: 1.
Attentional Bias Modification Training for People With Chronic Musculoskeletal Pain
ClinicalTrials.gov study NCT02232100. IPD Sharing: NO. Countries: 1. Publications: 1.
Spatial Neglect and Bias in Near and Far Space
ClinicalTrials.gov study NCT00350012. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Treatment of Social Phobia With Combined Cognitive Bias Modification and iCBT
ClinicalTrials.gov study NCT01570400. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Secondary Prevention of Depression Applying an Experimental Attentional Bias Modification Procedure
ClinicalTrials.gov study NCT02658682. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Study of the Effects of Oxytocin on Attentional Bias and Startle in PTSD
ClinicalTrials.gov study NCT03211013. IPD Sharing: NO. Countries: 1. Publications: 22.
Weight Bias Reducation Intervention With Nursing Students Using Simulation: The BRAVE Study
ClinicalTrials.gov study NCT07334470. IPD Sharing: UNDECIDED. Countries: 1. Publications: 50.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.