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8,038 results for “validation.”
Figure 6 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 6 Linearity of the developed RP-HPLC D_5d stability indicating method.
Figure 2 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 2 Chromatogram of standard solution of the analyzed hydrazone D-5d (tR = 6.110).
Figure 1 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 1 Structure of the selected model compound.
Dataset related to article "Apparent Diffusion Coefficient standardization: multi-center and multi-vendor validation study across 1.5T and 3T scanners in a diffusion MRI phantom"
<p>The dataset includes ADC measurements collected for MRI harmonisation across centers and vendors, performed as part of the multicenter RESPECT project, using the QIBA-NIST diffusion MRI phantom.</p> <p>The dataset includes the following sheets:</p> <p>"ADC" sheet: ADC measurements (averaged over 4 repeated measures) for each scanner, comprising both first and second acquisition and 3 imaging planes. </p> <p>"temperature" sheet: temperature measurement of the phantom for each acquisition session.</p> <p>"repeatability" sheet: ADC measurements of the 4 repeated measures for the first acquisition. Average values and CVs are also reported.</p>
Validation data for tttsa, automated tilt-series alignment in PyTorch
<p>This dataset contains a tilt-series ordered by tilt angle saved in mrc format (.st), and the corresponding tilt angles for the collection (.rawtlt). The approximate tilt-axis angle was -88.7 in the serial-em mdoc file.</p> <p>The dataset also contains a bash script to run AreTomo (v1.3.4) for the same tilt-series and an output alignment from AreTomo (.aln).</p>
FIG. 3 in (1833-1905): a discussion about their validity with some examples of nomenclatural consequences for the Gabonese flora in particular
FIG. 3. — Plesiatropha klaineana Pierre, drawing by E. DELPY, XI.1900. After a copy in P.
Figure 1 from: Kokanova-Nedialkova Z, Nedialkov P (2021) Validated UHPLC-HRMS method for simultaneous quantification of flavonoid contents in the aerial parts of Chenopodium bonus-henricus L. (wild spinach). Pharmacia 68(3): 597-601. https://doi.org/10.3897/pharmacia.68.e69781
Figure 1 Chenopodium bonus-henricus L.
Fig. 1 in Tridacna noae (Röding, 1798) - a valid giant clam species separated from T. maxima (Röding, 1798) by morphological and genetic data
Fig. 1. Map of Taiwan showing sampling sites for giant clams.
Figure 3 from: Bousquet Y, Messer P (2010) Redescription of Stenolophus thoracicus Casey (Coleoptera, Carabidae, Harpalini), a valid species. ZooKeys 53: 25-31. https://doi.org/10.3897/zookeys.53.470
Figure 3 - Collection localities for Stenolophus thoracicus.
Figure 2 from: Bousquet Y, Messer P (2010) Redescription of Stenolophus thoracicus Casey (Coleoptera, Carabidae, Harpalini), a valid species. ZooKeys 53: 25-31. https://doi.org/10.3897/zookeys.53.470
Figure 2 - Median lobe of aedeagus of Stenolophus thoracicus. a left lateral view b ventral view.
Figure 1 from: Bousquet Y, Messer P (2010) Redescription of Stenolophus thoracicus Casey (Coleoptera, Carabidae, Harpalini), a valid species. ZooKeys 53: 25-31. https://doi.org/10.3897/zookeys.53.470
Figure 1 - Habitus (dorsal view) of Stenolophus thoracicus.
Figure 5 from: Courtial C, Picard L, Ysnel F, Petillon J (2014) Validation of Eustiromastix guianae (Caporiacco, 1954) (Araneae, Salticidae) with a first description of the female, and additions to the salticid fauna of French Guiana. ZooKeys 420: 11-18. https://doi.org/10.3897/zookeys.420.6977
Figure 5 - Habitus of Eustiromastix guianae, male, fresh specimen (A) and female (B). Scale: 1 mm.
Figure 3 from: Courtial C, Picard L, Ysnel F, Petillon J (2014) Validation of Eustiromastix guianae (Caporiacco, 1954) (Araneae, Salticidae) with a first description of the female, and additions to the salticid fauna of French Guiana. ZooKeys 420: 11-18. https://doi.org/10.3897/zookeys.420.6977
Figure 3 - Drawing of Eustiromastix guianae epigyne (A dorsal view B ventral view). Scale 0.5 mm.
Figure 1 from: Gibson G (2013) The extinct Baltic amber genus Propelma Trjapitzin, a valid genus of Neanastatinae (Hymenoptera, Eupelmidae). ZooKeys 283: 59-69. https://doi.org/10.3897/zookeys.283.4665
Figure 1 - Propelma rhodendorfi, amber block bearing holotype female.
Figure 29 from: Ghittino C, Busato E, Casale A (2015) Re-establishment of Carabus (Cathoplius) aliai Escalera, 1944 as a separate valid species (Coleoptera, Carabidae). ZooKeys 496: 61-84. https://doi.org/10.3897/zookeys.496.9428
Figure 29 - Distribution map of Carabus (Cathoplius) aliai Escalera, 1944 and its sister species.
Supplementary Website, Data, and Scripts for the Paper "Automatic Core-Developer Identification on GitHub: A Validation Study"
<p>Supplementary website containing result plots, pseudonymized input data, resulting pseudonymized classification data, analysis scripts, and Dockerfile used to produce the results of the paper "Automatic Core-Developer Identification on GitHub: A Validation Study".</p> <p>The pseudonymized input data is also availble separately here: https://zenodo.org/record/7775078</p> <p>The resulting pseudonymized classification data is also available separately here: https://zenodo.org/record/7775385</p>
Validation of StrainIQ software performance using metagenomic data from ATCC staggered mix genomes
<p>StrainIQ (Strain Identification and Quantification) is a novel tool that implements a new <em>n</em>-gram based algorithm for predicting and quantifying strain-level taxa from whole genome metagenomic sequencing data. We tested our method using simulated (GI tract reference genomes) and mock metagenomic datasets (from ATCC microbial genomic mix) and compared its performance with existing methods. Here, the gut_mix.zip file contains the metagenomic sequence data from the ATCC 20 strain staggered genomic mix (MSA-1003). From this original sequencing sequence (nearly 120X), we created additional datasets with 90X, 60X, 30X, 5X, 3X, and 1X coverage and tested StrainIQ performance on those varying sequencing datasets.</p> <p>Please find the new link for this data at https://zenodo.org/record/8132164</p>
Results of cross-validation by Mlflow for "Can the audience understand a business process model? Using Random Forest to classify level understandability based on personal and model factors"
<p>This dataset of results contains a summary of the evaluation metrics for each fold, including information about hyperparameter tuning.</p>
WHUS2-CRv a global thin cloud removal dataset for Sentinel-2 images——Validation and testing parts
<p>The validation and testing parts of WHUS2-CRv dataset in which the paired cloud and cloud-free Sentinel-2 images are from different regions of the world. The types of land cover are rich and the acquisition dates of the experimental data cover a long time period (from 2015 to 2020) and all seasons.</p> <p>If you use this dataset for your research, please cite us accordingly:</p> <p>#Reference: </p> <p>[1]J. Li, Z. W, Z. Hu, J. Z, M. Li, L. Mo and M. Molinier, “Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion,” ISPRS J. Photogramm. Remote Sens., vol. 166, pp. 373-389, Aug. 2020,http://doi.org/10.1016/j.isprsjprs.2020.06.021.</p> <p>[2]J. Li, Z. Wu, Z. Hu, Z. Li, Y. Wang, and M. Molinier, “Deep learning based thin cloud removal fusing vegetation red edge and short wave infrared spectral information for Sentinel-2A imagery,” Remote Sens., vol. 13, no. 1, p. 157, Jan. 2021, http://doi.org/10.3390/rs13010157.</p> <p>[3]J. Li, Y. Zhang, Q. Sheng, Z. Wu, B. Wang, Z. Hu, G. Shen, M. Schmitt, M. Molinier, “Thin Cloud Removal Fusing Full Spectral and Spatial Features for Sentinel-2 Imagery,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 8759-8775, 2022, doi: 10.1109/JSTARS.2022.3211857.</p>
Sint Maartenskliniek - IMU Gait Analysis (Validation study, release tag v1.1.0)
<p>https://github.com/SintMaartenskliniek/IMU_GaitAnalysis/releases/tag/v1.1.0</p>
ScienceDex guides
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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)
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.