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12,753 results for “Corrections”
Inner filter effect correction for fluorescence measurements in microplates (AddAbs) - experimental data
<p>Experimental data for the paper entitled <em>Reducing the Inner Filter Effect in Microplates by Increasing Absorbance? Linear Fluorescence in Highly Concentrated Fluorophore Solutions in the Presence of an Added Absorber</em> (<a href="https://doi.org/10.1021/acs.analchem.3c01295">https://doi.org/10.1021/acs.analchem.3c01295</a>).</p> <p>Separate worksheets are provided for the following:</p> <p>1. Fluorescence measurements - raw values in triplicate; 2 worksheets for transparent (T) and nontransparent (NT) microplates, each with 15 titrations: L<sub>1</sub>-L<sub>12</sub> and H<sub>1</sub>-H<sub>3</sub>,</p> <p>2. Absorbance measurements - raw values in triplicate (<em>λ</em><sub>ex</sub> = 345 nm, <em>λ</em><sub>em</sub> = 390 nm); 1 worksheet for T microplates only, with 4 titrations: L<sub>1</sub>-L<sub>4</sub>,</p> <p>3. Fluorescence measurements - averaged, baseline-corrected averaged and normalized baseline-corrected averaged triplicates; 2 worksheets for T and NT microplates, each with 15 titrations: L<sub>1</sub>-L<sub>12</sub> and H<sub>1</sub>-H<sub>3</sub>,</p> <p>4. ZINFE/NINFE-corrected fluorescence in T microplates; 12 worksheets for 12 titrations: L<sub>1</sub>-L<sub>9</sub> and H<sub>1</sub>-H<sub>3</sub>,</p> <p>5. ZINFE/NINFE-corrected fluorescence in NT microplates; 12 worksheets for 12 titrations: L<sub>1</sub>-L<sub>9</sub> and H<sub>1</sub>-H<sub>3</sub>.</p> <p>The results of the ZINFE and NINFE correction methods obtained using the online calculator service written in Javascript: https://ninfe.science (version 09.5.2022.)</p> <p>For additional details please visit: https://glymech.pharma.hr//GlyMech.html.</p>
Bioclimatic outputs for Last Glacial Maximum South America for LPX, bias-corrected to pollen records
<p>LPX model output for South America for the Last Glacial Maximum. We provide outputs for LPX driven by four GCM simulated climates along with an ensemble average:</p> <ul> <li>MIROC.tar.gz: LPX driven by MIROC3.2</li> <li>FGOALS.tar.gz: driven by FGOALS-1.0g</li> <li>HAD.tar.gz: HadCM3M2</li> <li>CNRM.tar.gz: CNRM-CM33</li> <li>Ensemble.tar.gz: The mean of each output variable for the four models.</li> </ul> <p> </p> <p>Driving data comes from the Palaeoclimate Modelling Intercomparison Project Phase II (PMIP2)<sup>1,2</sup>. See Sato et al. <sup>3</sup> for modelling protocol.</p> <p>Each model’s directory contains “uncorrected” and “corrected” directories. With each of these are bioclimatic maps outputted from LPX and biome information:</p> <ul> <li>fpc.nc: fractional projected cover of all vegetation</li> <li>height.nc: mean height of vegetations</li> <li>gdd.nc: Growing Degree Days base 2</li> <li>tropical.nc: proportion of vegetated areas taken up by tropical trees and c4 grasses</li> <li>temperate.nc: proportion of vegetated areas taken up by temperate trees and c3 grasses</li> <li>evergreen.nc: proportion of tree cover that is composed of evergreen trees</li> <li>biome.nc: the assigned biomes from these data, based on a modified version of Sato et al. <sup>3</sup>. See “biomisation” below.</li> <li>cluster.nc: In “corrected” only. The spatial location of kmean clusters of fpc vs height. See <sup>4</sup> for details.</li> </ul> <p> </p> <p>“Uncorrected” is from Sato et al. <sup>3</sup>. “Corrected” is bias-corrected to match the 42 pollen-core observations taken from Marchant et al. <sup>5</sup> We do this by shifting the total vegetation cover and composition, height, and growing degree day (GDD) DVM output to the closest boundary of the corresponding biome of the pollen core in that specific location. We then extrapolate this correction between pollen-core locations across the Neotropics. See Kelley et al. <sup>4</sup> for details.</p> <p> </p> <p><strong>Biomeisation</strong></p> <p>"Biomeisation.png" displays the scheme. We primarily split biomes by FPCs of 0.3 and 0.6, with biomes > 0.6 split by a height of 10m. Forests (>0.6 FPC and > 10m) is split by GDD, Evergreen FPC (EG) and Tropical or temperate FPC (TR, TM). Likewise, we split FPCs> 0.6 and heights <10m into savanna, woodland and parkland using EG and TR. We additionally assign Tropical savanna >5m to Woodland/Tropical savanna. We divided desert, dry grassland and (shrub)-tundra by FPC of 0.3 and GDD of 350°C. See Kelley et al. <sup>4</sup> for details.</p>
UKCP18 RCM precipitation and temperature bias corrected using ISIMIP3BA change-preserving quantile mapping.
<p>We present bias-corrected UK Climate Projections 2018 (UKCP18; Met Office Hadley Centre, 2018) regional datasets for temperature, precipitation, and potential evapotranspiration (1981-2080). All 12 members of the 12 km ensemble were corrected using quantile mapping and a change-preserving variant (Lange, 2019; Lange, 2020). Both methods effectively reduce biases in multiple statistics, while maintaining projected climatic changes. We provide guidance on using the bias-corrected datasets for climate change impact assessment. Please find a detailed description and evaluation in the metadata and accompanying data paper (Reyniers et al., 2025).</p> <p>---</p> <p>Met Office Hadley Centre (2018): UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080. CEDA, <em>8 March 2022</em>. <a href="https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604">https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604</a></p> <p>Lange, S. (2019). Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1. 0). <em>GMD,</em> <em>12</em>(7), 3055-3070.</p> <p>Lange, S. (2020). ISIMIP3BASD (2.4.1). Zenodo. https://doi.org/10.5281/zenodo.3898426</p> <p>Reyniers, N., Zha, Q., Addor, N., Osborn, T. J., Forstenhäusler, N., & He, Y. (2025). Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain. <em>Earth System Science Data</em>, <em>2025, 17(5)</em>, 2113–2133.</p>
Fig. 2 in Pupa menkeana Pfeiffer, 1853, type species of the speciose land snail genus Gulella Pfeiffer, 1856: correction of longstanding PLVLGHQWL¿FDWLRQ DQG GHVLJQDWLRQ RI QHRW\SH (Mollusca: Eupulmonata: Streptaxidae)
Fig. 2. (A, B) lectotype and paralectotype of Ennea adamsiana Pfeiffer, 1859 in 1854–1860, 'Port Natal, M.C. [Mus. Cuming]', length 8.45 and 8.1 mm (NHMUK 20110168); (C, D) syntypes of Ennea impervia Melvill & Ponsonby, 1896, 'Natal', length 8.8 and 8.75 mm (NHMUK 1903.3.11.85–86); (E) holotype of Ennea aurisleporis Melvill & Ponsonby, 1898, 'Natal', length 6.65 mm (NHMUK 1903.3.11.69); (F) holotype of Ennea socratica Melvill & Ponsonby, 1893, 'Pietermaritzburg', length 8.45 mm (NHMUK 1903.3.11.78); (G) Gulella menkeana, small inland form, Cumberland, Pietermaritzburg, length 7.2 mm (NMSA V9709); (H) G. menkeana, large form from coastal E. Cape, Port St Johns, length 9.24 mm (NMSA W561); (I) Pupa wahlbergi Krauss, 1848, probable paratype in SMNH, length 10.1 mm (SMNH-Type-2112); (J, K) P. wahlbergi Krauss, 1848, neotype, Durban Bluff, length 9.84 mm, diameter 4.92 mm (NMSA W7942/T2669); (L) holotype of Ennea formosa Melvill & Ponsonby, 1898, Pietermaritzburg, length 7.75 mm (NHMUK 1903.3.11.79).
Reactive Correction of Object Placement Errors for Robotic Arrangement Tasks (Video)
<p>Supplementary video for the paper "Reactive Correction of Object Placement Errors for Robotic Arrangement Tasks".</p>
Data for "Global Precipitation Correction Across a Range of Climates Using CycleGAN"
<p># Data for "Global Precipitation Correction Across a Range of Climates Using CycleGAN"</p> <p>This repository contains the data used in the paper "Global Precipitation Correction Across a Range of Climates Using CycleGAN" by J. McGibbon et al. (2023, *in review*).</p> <p>`train_val` contains the model outputs for the training and validation sets used in the paper. Model spinup data is not included. The C384 runs are stored as a single series along a concatenated time axes. All C384 data has been coarsened to C384 resolution.</p> <p>`ramping_data` contains the model outputs from the 4-year, 3-month ramping simulation, including spinup data.</p> <p>`predicted` is included for convenience, and contains the model outputs from the "best" model, as was used to create figures shown in the paper. This model output was created from the CycleGAN using the validation dataset (stored in `train_val`) as input, and years 2 and 3 of the ramping simulation in `ramping_data` (following the 3-month spinup period). Ramping predictions are stored as separate datasets for the C48 (backwards) prediction and the C384 prediction. Validation data is stored alongside its respective target data in a single netCDF file, labelled "processed-agg". These filenames are intentionally left unchanged so that they correspond with the names of files used in the `process_combined_aggregate.py` script in `projects/cyclegan` of the code DOI for this paper, which was used to create its figures.</p>
MultiScent-20 Data - Binary responses (correct vs. incorrect answers) data from full sample, for each odour
<p>Data used for IRT analysis in the article</p> <p>"The Multiscent-20: A Digital Odour Identification Test Developed with Item<br> Response Theory", with the following authors:</p> <p>Marcio Nakanishi 1, *, Pedro Renato de Paula Brandão 2, *, Gustavo Subtil Magalhães<br> Freire 1 , Luis Gustavo do Amaral Vinha 3 , Marco Aurélio Fornazieri 4 , Wilma Terezinha<br> Anselmo Lima 5 , Claudia Galvão 6 , Thomas Hummel 7</p> <p> </p> <p>1 Department of Otorhinolaryngology, University Hospital of Brasília, University of<br> Brasília, Brasília, DF, Brazil<br> 2 Neurology Department, Hospital Sírio-Libanês, Brasília, DF, Brazil<br> 3 Statistics Department, University of Brasília, DF, Brazil<br> 4 State University of Londrina, Pontifical Catholic University of Paraná<br> 5 Department of Ophthalmology and Otorhinolaryngology, Ribeirão Preto Medical<br> School-University of São Paulo, Brazil<br> 6 NOAR Brasil Ltda, São Paulo-SP, Brazil<br> 7 Smell and Taste Clinic, Department of Otorhinolaryngology, Technical University of<br> Dresden, Dresden, Germany</p> <p> </p> <p> </p> <p>MultiScent-20 descrition:</p> <p>The Multiscent-20 is a portable tablet computer with an integrated hardware<br> system consisting of a central processing unit, touchscreen, Wi-Fi antenna, USB dock,<br> power supply, and rechargeable battery. Additionally, it contains an odour system<br> composed of 20 microcartridges, an air filter, a system that generates a dry air stream,<br> and an odour-dispensing opening. The device is capable of presenting 20 different<br> odours from individual odour capsules, which store the olfactory stimuli by incorporating<br> the odours into an oil-resistant polymer. The capsules are loaded through an insertion<br> port on the back of the device.<br> A software-controlled processing unit governs the flow of dry air, generating a<br> constant air stream that passes through the capsule, releasing individual odours<br> through a small opening at the upper front of the device. In this study, each scent was<br> presented for 5 seconds, with an interval of at least 6 seconds between odour<br> presentations. Each capsule contained 35 µL of oil-based odour solution, allowing the<br> device to maintain consistent odour intensity and identifiability for up to 100 activations,<br> as per the manufacturer's instructions. The Givaudan Flavours and Fragrance<br> Corporation (São Paulo, Brazil) prepared the odours used in the capsules.<br> A digital application (software) was developed to present odours and record<br> olfactory function test results. The device delivers odours through a dry air system,<br> leaving no residue in the environment or on users. Users can access the test using an<br> application on the device (screen version) or mobile phone. The results are accessible<br> through the integrated software, allowing for storage and analysis of the data.</p>
Figs 1–9 in New Records Of Poemeniinae And Xoridinae (Hymenoptera, Ichneumonidae) From Ukraine And Poland, With Corrections To The Ukrainian Checklist
Figs 1–9. Xorides spp.: 1–2, 4, 6 — X. corcyrensis (holotype female); 3, 5, 7 — X. fasciipennis (holotype female); 1 — antenna; 2 — wings; 3 — antenna and wings; 4–5 — metasomal tergites 1–3 (dorsal view); 6–7— type labels; 8 — X. stepposus (dorsal view of female habitus); 9 — X. depressus (lateral view of male habitus).
Fig. 10 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 10. Apobaetis luanae sp. nov., holotype (INPA), mouthparts of nymph. A. Labrum (left d.v., right v.v). B. Detail of simple medial spine-like setae on dorsal surface of labrum. C. Detail of short medial spine-like setae on ventral surface of labrum. D. Left mandible. E. Detail of setae on process subtriangular base of left mandible. F. Right mandible. G. Hypopharynx. H. Maxilla. I. Labium (left d.v., right v.v.). Abbreviations: d.v. = dorsal view; v.v. = ventral view. Not to scale.
Fig. 11 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 11. Apobaetis luanae sp. nov., holotype (INPA), thorax and abdomen of nymph. A. Foreleg (femur on anterior surface). B. Detail of setae on anterior surface of forefemur. C. Claw. D. Posterior margin of tergum IV. E. Gill. F. Paraproct. G. Cercus. H. Paracercus. Not to scale.
Fig. 9 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 9. Apobaetis luanae sp. nov., holotype (INPA), habitus of nymph. A. Nymph male (d.v.). B. Nymph male (v.v.). Abbreviations: d.v. = dorsal view; v.v. = ventral view. Not to scale.
Fig. 8 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 8. Apobaetis jaquelinae sp. nov., holotype (INPA), thorax and abdomen of nymph. A. Foreleg (femur on anterior surface). B. Detail of setae on anterior surface of forefemur. C. Claw. D. Posterior margin of tergum IV. E. Gill. F. Paraproct. G. Cercus. H. paracercus. Not to scale.
Fig. 7 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 7. Apobaetis jaquelinae sp. nov., holotype (INPA), mouthparts of nymph. A. Labrum (left d.v., right v.v). B. Detail of medial spatulate setae on dorsal surface of labrum. C. Left mandible. D. Right mandible. E. Hypopharynx. F. Maxilla. G. labium (left d.v., right v.v.). Abbreviations: d.v. = dorsal view; v.v. = ventral view. Not to scale.
Fig. 6 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 6. Apobaetis jaquelinae sp. nov., habitus of nymph. A–B. Holotype (INPA). A. Nymph male (d.v.). B. Nymph male (v.v.). C. Paratype (INPA), Nymph female (d.v.). Abbreviations: d.v. = dorsal view; v.v. = ventral view. Not to scale.
Fig. 4 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 4. Apobaetis pasternakae sp. nov., holotype (INPA), mouthparts of nymph. A. Labrum (left d.v., right v.v). B. Detail of medial spatulate setae on dorsal surface of labrum. C. Left mandible. D. Right mandible. E. Hypopharynx. F. Maxilla. G. Labium (left d.v., right v.v.). Abbreviations: d.v. = dorsal view; v.v. = ventral view. Not to scale.
Fig. 2 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 2. Apobaetis fiuzai Salles & Lugo-Ortiz, 2002, habitus of nymph, from different populations, showing pigment variation. A–F. Goiás State. A. Nymph female (d.v.). B. Nymph female (v.v.). C. Nymph female (d.v.). D. Nymph female (v.v.). E. Nymph male (d.v.). F. Nymph male (v.v.). – G–H. Piauí State. G. Nymph female (d.v.). H. Nymph female (v.v.). – I–O. Bahia State. I. Nymph female (d.v.). J. Nymph female (v.v.). L. Nymph female (d.v.). M. Nymph female (v.v.). N. Nymph female (d.v.). O. Nymph female (v.v.). Abbreviations: d.v. = dorsal view; v.v. = ventral view. Not to scale.
Fig. 1 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 1. Map with distribution of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 (including putative records) (black circles), Apobaetis pasternakae sp. nov. (yellow stars), Apobaetis kallawaya Nieto, 2006 (green square), Apobaetis jaquelinae sp. nov. (red triangles), and Apobaetis luanae sp. nov. (blue triangles).
Fig. 3 in Additions and corrections to taxonomy of Apobaetis fiuzai Salles & Lugo-Ortiz, 2002 and Apobaetis kallawaya Nieto, 2006 (Ephemeroptera, Baetidae)
Fig. 3. Apobaetis pasternakae sp. nov., habitus of nymph. A–C. Holotype (INPA). A. Nymph female (d.v.). B. Nymph female (v.v.). C. Nymph female (l.v.). D–N. Pigment variation in different populations. D–I. Amazonas State.D. Nymph female (d.v.). E. Nymph female (v.v.). F. Nymph male (d.v.). G. Nymph male (v.v.). H. Nymph male (d.v.). I. Nymph male (v.v.). J–N. Roraima State. J. Nymph female (d.v.). L. Nymph female (v.v.). M. Nymph female (d.v.). N. Nymph female (v.v.). Abbreviations: d.v. = dorsal view; l.v. = lateral view; v.v. = ventral view. Not to scale.
Steady VLM correction exemplar
<p>This dataset includes an example MATLAB script that implements corrections to steady Vortex Lattice Method (VLM) results. Corrections include:</p> <ol> <li>Viscous lift curve slope.</li> <li>Lifting surface viscous drag (including lift-dependent viscous drag).</li> <li>Fuselage profile drag.</li> <li>Fuselage contribution to pitching moment.</li> <li>Tailplane contribution to pitching moment.</li> </ol> <p>The example includes experimental wind tunnel data from a model of an English Electric Canberra, along with software models of this aircraft in three popular steady VLM solvers: AVL, XFLR5 and OpenVSP/VSPAERO. </p>
TCSIF: A temporally consistent global GOME-2A SIF dataset with correction of sensor degradation
<p><strong>TCSIF: A temporally consistent global GOME-2A SIF dataset with correction of sensor degradation</strong></p> <p> </p> <p><strong>Description:</strong></p> <p>The global monthly GOME-2A SIF dataset (2007–2021) with correction of temporal degradation. The corrected global GOME-2 SIF dataset can be obtained in two types. The daily level2 dataset is provided in hdf5 format(compressed in the zip files named "{Year}{Quater}.zip"). The name of the hdf5 files was SIF_daily_YYYYMMDD.h5, YYYY, MM, and DD represent the year, month, and date, respectively. The level3 datasets which were aggregated monthly from the level2 dataset, have a spatial resolution of 0.5°and were saved in TIFF format in chronological order from 2007 to 2021 (compressed in the file "Level3.zip"). The name of the files was SIFpar_evi_monthly _YYYYMM.tif, where SIF was product type, par, and evi represented upscaled parameters, monthly represented temporal scale, YYYY and MM was the year and month, respectively. The SIF output was stored in the hdf5 files along with other variables of interest for further processing and visualization. See the appendix for the structure of the hdf5 file.</p> <p> </p> <p><strong>cloud_fraction</strong><strong>[float]</strong>:</p> <p>Description: Effective cloud fraction derived from GOME-2 Level1B product.</p> <p>Units: none</p> <p><strong>latitude</strong><strong>[float]</strong>:</p> <p>Description: Pixel center latitude.</p> <p>Units: degrees N</p> <p><strong>longitude</strong><strong>[float]</strong>:</p> <p>Description: Pixel center longitude.</p> <p>Units: degrees E</p> <p><strong>latitude_bounds</strong><strong>[float]</strong>:</p> <p>Description: Latitude of the boundary corners for each pixel.</p> <p>Units: degrees N</p> <p><strong>longitude _bounds</strong><strong>[float]</strong>:</p> <p>Description: Longitude of the boundary corners.</p> <p>Units: degrees E</p> <p><strong>SIF_740</strong><strong>[float]</strong>:</p> <p>Description: SIF signal at 740nm retrieved using the 735–758 nm fitting window.</p> <p>Units: mW m<sup>-2</sup> nm<sup>-1</sup> sr<sup>-1</sup></p> <p><strong>SIF_daily</strong><strong> [float]</strong>:</p> <p>Description: SIF signal at 740nm with correction of day-length.</p> <p>Units: mW m<sup>-2</sup> nm<sup>-1</sup> sr<sup>-1</sup></p> <p><strong>Sigma_i</strong><strong>[float]</strong>:</p> <p>Description: The squre of single retrieval error of SIF_740.</p> <p>Units: (mW m<sup>-2</sup> nm<sup>-1</sup> sr<sup>-1</sup>)<sup>2</sup></p> <p><strong>Solar_zenith_angle</strong><strong> [float]</strong>:</p> <p>Description: Solar zenith angle.</p> <p>Units: degrees</p> <p><strong>Solar_azimuth_angle</strong><strong> [float]</strong>:</p> <p>Description: Solar azimuth angle.</p> <p>Units: degrees</p> <p><strong>Viewing _zenith_angle</strong><strong> [float]</strong>:</p> <p>Description: Viewing zenith angle.</p> <p>Units: degrees</p> <p><strong>Viewing_azimuth_angle</strong><strong>[float]</strong>:</p> <p>Description: Viewing azimuth angle.</p> <p>Units: degrees</p> <p><strong>chi2</strong><strong>[float]</strong>:</p> <p>Description: The reduced chi-square value calculated based on the the fitting residuals.</p> <p>Units: None</p> <p><strong>Rad_NIR</strong><strong>[float]</strong>:</p> <p>Description: The average radiance within the 735~758 nm window</p> <p>Units: mW m<sup>-2</sup> nm<sup>-1</sup> sr<sup>-1</sup></p> <p><strong>ps_NIR</strong><strong>[float]</strong>:</p> <p>Description: The average reflectance within at around 680 nm ().</p> <p>Units: None</p> <p><strong>ps_red</strong><strong>[float]</strong>:</p> <p>Description: The average reflectance within the 665~680 nm window</p> <p>Units: None</p> <p><strong>NDVI</strong><strong>[float]</strong>:</p> <p>Description: Calculated by the TOA reflectance at red band (around 680 nm) and near-infrared band (around 780nm).</p> <p>Units: None</p> <p><strong>QA</strong><strong>[int]</strong>:</p> <p>Description: Quality_flag.</p> <p>0= Bad (ineffective original data)</p> <p>1= Good (passed all quality-filtering criteria)</p> <p>2= Good and the cloud fraction is lower than 0.3</p> <p>Units:None</p>
ScienceDex guides
Understand access before you commit
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)
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.