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1,663 results for “BIAS”
Six-decade research bias toward fancy and familiar bird species
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Lying in a 3T MRI scanner induces neglect-like spatial attention bias
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Spatial survival analysis accounts for female-biased breeding dispersal and provides realistic estimates of true annual survival in migratory warblers
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Cryptic species can be phylogenetically old despite strong sex-biased dispersal
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Data from: An analysis of mating biases in trees
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Data from: Female-biased population sex ratios caused by genetic rather than ecological mechanisms in dwarf willow (Salix herbacea L.)
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Data from: Sex bias in mortality risk changes over the lifespan of bottlenose dolphins
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Ignoring within-flower self-fertilization and inbreeding depression biases estimates of selection on floral traits
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Seasonal but not sex-biased gene expression of the carotenoid ketolase, CYP2J19, in the sexually dichromatic southern red bishop (Euplectes orix)
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Predicting sex bias in mobility from functional traits in flying insects
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Naturalization of introduced plants is driven by life-form-dependent cultivation biases
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Data from: Integrated species distribution models to account for sampling biases and improve range wide occurrence predictions
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Developmental bias in the evolution and plasticity of beetle horn shape
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Piecewise continuous sampling: a method for minimizing bias and sampling effort for estimated metrics of animal behavior
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Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination
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LAGOS Lake nutrient, carbon and chlororphyll data to evaluate biases in lake water quality sampling practices in a 17-state region of the US
This dataset includes data for eight major limnological variables in LAGOS-NE_LIMNO v. 1.087.1 that were used to evaluate biases in lake water quality sampling and implications for macroscale research (Stanley et al. In Revision, Limnology and Oceanography). Most observations came from LAGOS-NE_LIMNO v. 1.087.1, an integrated database of lake ecosystems (Soranno et al. 2015, Soranno et al. 2017) but were supplemented with additional data from the State of New Hampshire. LAGOS-NE contains information on lakes great than or equal to 1 ha (originally derived from the U.S. Geological Survey's 2013 National Hydrography Dataset) for a 17-state region of the U.S., and a subset of the lakes has observational data on lake chemistry and productivity. Approximately 87 different sources of data were compiled for the LAGOS-NELIMNO v. 1.087.1 dataset and were mostly generated by government agencies (state, federal, tribal) and universities. In this analysis, we compiled data for eight major limnological variables (Secchi disk depth, chlorophyll, total phosphorus, total nitrogen, nitrate, ammonium, true water color, and dissolved organic carbon) and geographic characteristics of lakes (location, lake area, depth, perimeter, watershed area) to evaluate biases in different limnological properties over space and time.
Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅱ
<p>A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region.</p> <p><strong>Note: For Tmin in historical periods, the values larger than 2606 refer to no data. Set them to NaN before using, for example (Matlab): Tmin(Tmin>2606)=nan;</strong></p> <p>More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.</p>
Dataset of trend-preserving bias-corrected daily temperature, precipitation and wind from NEX-GDDP and CMIP5 in the Qinghai-Tibet Plateau——Part Ⅰ
<p>A bias-corrected dataset containing daily meteorological data of the Qinghai-Tibet Plateau has been generated, by using a trend-preserving bias-correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach together with a high-quality gridded meteorological dataset based on ground observation (CN05.1). The data set contains daily bias-corrected values of maximum/minimum near-surface air temperature, precipitation and mean near-surface wind speed from 15 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) and their downscaled high-resolution dataset (NEX-GDDP) in the Qinghai-Tibet Plateau (QTP) during 1986-2095. This dataset can provide important reference for the study on future climate change and its impacts in the Qinghai-Tibet Plateau region.</p> <p><strong>Note: For Tmax in historical periods, the values larger than 2606 refer to no data. Set them to NaN before using, for example (Matlab): Tmax(Tmax>2606)=nan;</strong></p> <p>More details about this dataset can be found in the article: S. Chen, T. Ye, W. Liu, A. Wang and P. Shi. Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Tibet plateau[J], Plateau Meteorology (in Chinese), 2020, DOI: 10.7522/j.issn.1000-0534. 2020. 00019.</p>
Air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This data set contains the air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017. The data are provided over overlapping wind direction secotors of 5(10) degree width stepped by 1(2) degrees relative wind direction. These bias factors can be used to correct the observed wind speeds for air-flow distortion on a sample by sample basis. For details see Landwehr et al. (2019; DOI: https://doi.org/10.5194/amt-2019-366).</p> <p><strong>Dataset contents</strong></p> <ul> <li>flow_distortion_bias_sensor1.csv, data file, comma-separated values</li> <li>flow_distortion_bias_sensor2.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This dataset of air-flow distortion factors is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Data for journal article: "Automated precipitation monitoring with the Thies disdrometer: Biases and ways for improvement"
<p>This dataset contains data used for the journal article" Automated precipitation monitoring with the Thies disdrometer: Biases and ways for improvement" submitted to Atmospheric Measurement Techniques.</p>
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.