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2,129 results for “scores”
FIG. 7. — Discriminant score D in A taxonomic revision of the ant subgenus Coptoformica Mueller, 1923 (Hymenoptera, Formicidae)
FIG. 7. — Discriminant score D(5) calculated with the characters sqrtPDF, sqrtPDG, SL/CL, ML, and GLANZ to separate Formica foreli and pressilabris queens. The bars mark the position of the following type material: n, type series of F. naefi Kutter; g, type series of F. goesswaldi Kutter; t, paratype of F. tamarae Dlussky.
FIG. 6. — Discriminant score D in A taxonomic revision of the ant subgenus Coptoformica Mueller, 1923 (Hymenoptera, Formicidae)
FIG. 6. — Discriminant score D(4) calculated with the characters sqrtPDF, sqrtPDG, SL/CS, and TERG to separate Formica foreli and pressilabris worker nest samples; the bars mark the position of the following type material: n, type series of F. naefi Kutter, 1957; g, type series of F. goesswaldi Kutter, 1967; f, holotype of F. foreli Emery, 1909; t, topotypical series of F. tamarae Dlussky, 1964; p, type series of F. pressilabris Nylander, 1846.
Text-fig. 7. Plot of discriminant scores (R1/R2) of individual M1 of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of total set of characters, both metric and non-metric). in Genus Apodemus In The Pleistocene Of Central Europe: When Did The Extant Taxa Appear?
Text-fig. 7. Plot of discriminant scores (R1/R2) of individual M1 of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of total set of characters, both metric and non-metric).
Text-fig. 8. Plot of discriminant scores (R1/R2) of individual m1 of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (standardized discrimination scores based on nine most significant variables). in Genus Apodemus In The Pleistocene Of Central Europe: When Did The Extant Taxa Appear?
Text-fig. 8. Plot of discriminant scores (R1/R2) of individual m1 of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (standardized discrimination scores based on nine most significant variables).
Text-fig. 6. Plot of discriminant scores (R1/R2) of individual m1 and M1 teeth of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of metric variables of M1 and m1). in Genus Apodemus In The Pleistocene Of Central Europe: When Did The Extant Taxa Appear?
Text-fig. 6. Plot of discriminant scores (R1/R2) of individual m1 and M1 teeth of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of metric variables of M1 and m1).
Scottish hill farming score by agricultural parishes
<p>Dataset to accompany work on the impact of hill farming in Scotland commissioned by RESAS (Scottish Government). Data resolution is agricultural parishes, spatial data defining these can be downloaded from <https://data.gov.uk/dataset/939fdd5e-7322-4ab7-9dc9-bbfc538c4477/agricultural-parishes>.</p> <p>Data used to define the hill farming score is derived from the following datasets: Ordnance Survey Terrain 50; Scottish Natural Heritage, landscape character assessment, carbon and peatland map; James Hutton Institute land capability for agriculture; RESAS agricultural census common and rough grazing areas.</p> <p>Licence statements for input data are:</p> <p>Derived from or contains: Scottish Government and SNH information licensed under the Open Government Licence v3.0; James Hutton Institute materials licensed under the Open Government Licence v.2.0; and Ordnance Survey data Crown copyright and database right 2018.</p> <p>Generation code can be found here: https://doi.org/10.5281/zenodo.1887477</p>
Automated Nuclear Pleomorphism Scoring in Breast Cancer: Slide-Study test set
<p>This dataset contains data from the Slide-Study data set used in the paper:</p> <p>[1]<em> C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. M. Horlings, W. Weichert, J. M. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J.-M Bokhorst, J. van der Laak, F. Ciompi, Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. NPJ Breast Cancer, 2022.</em></p> <p>The dataset consists of n=118 digital pathology whole-slide images (WSI) of breast cancer surgical resections, stained with hematoxylin and eosin (H&E) at Radboud University Medical Centers, Nijmegen (The Netherlands).</p> <p>The WSIs were scanned with a 3DHistech P1000 scanners at 0.25 um/px spacing, originally stored in MRXS file format. However, the WSIs made available here have been converted to TIFF format with a maximum spacing of 0.5 um/px. This was done to make slides broadly accessible (since MRXS files are sometimes not compatible with some digital pathology viewers or APIs), and with the same spacing used in the prediction of the pleomorphism score in the NPJ breast cancer paper.</p> <p>Note that we are solely releasing the Slide-Study test set used in [1]. Together with the data, we have released a web-based evaluation platform via the <a href="https://grand-challenge.org/">grand-challenge.org</a> platform, which can be found at this link: <a href="https://breastpleomorphism.grand-challenge.org/">https://breastpleomorphism.grand-challenge.org/</a>. In this way, researchers can download the WSI from Zenodo, process them with their algorithm to predict a single pleomorphism score for each slide, compile the predictions as indicated on the grand-challenge.org page, and submit them, to compare the results with the ones presented in the paper and with the opinion of a panel of four pathologists involved in the study.</p> <p>The data is released under CC BY-NC 4.0 license.</p>
SCoRe - Prototyp 2.2 - Erprobung des Forschungsszenarios "Urbane Grünflächen" - UGF-2
<p>Dieses Datenset enthält Materialien (Videos, Protokolle und Fallbeschreibungen) aus der zweiten prototypischen Durchführung des Forschungsszenarios "Urbane Grünflächen" im Teilprojekt <a href="http://www.360total.de/score/">SCoRe-VideoLearning</a> des <a href="https://scoreforschung.com/ueber/">Score-Projektes</a> ..</p> <p>Hierin finden sich drei exemplarische Fälle von Studierenden, welche sich videografisch forschend mit urbanen Grünflächen auseinandersetzten und dabei die Merkmale der Grünfläche hinsichtlich urbanen Nutzungsmöglichkeiten und der biologischen Vielfalt untersuchten. Dazu wurden die Grünflächen zunächst ausgewählt und in Bezug auf verschiedene vorgegebene Ordnungskriterien beschrieben und bewertet (Fallbeschreibung). Zur Produktion der Videoforschungsdaten - als Basismaterial der empirischen Untersuchung - waren die Studierenden angehalten ein Produktionsprotokoll während aller drei Produktionsphasen der Videografie (Vorproduktion, Produktion im Feld sowie Nachproduktion) auszufüllen und somit für sich sowie andere analysierende Studierende die Entscheidungsprozesse zur Gestaltung der Videoforschungsdaten zu explizieren und zu dokumentieren.. Diese Protokolle bilden entsprechend die Grundlagen für Gütekriterien qualitativer Forschungsdaten: Transparenz und intersubjektive Nachvollziehbarkeit (vgl. <a href="https://scoreforschung.files.wordpress.com/2022/03/score-vl-wirkungsbericht-3-zur-summativen-evaluation-des-prototypen-3_mhh-2.pdf">Wirkungsbericht 3</a>).</p>
Dataset for: Similarity scores of vibrational spectra reveal the atomistic structure of pentapeptides in multiple basins
<p>This dataset provides input/output files and scripts for the publication: Similarity scores of vibrational spectra reveal the atomistic structure of pentapeptides in multiple basins.</p>
Power of Place - National - Environmental and social impact score datasets
<p>Raster environmental and social datasets for Power of Place - National study as rasters for wind and solar PV. See technical slide deck on the Power of Place National website (The Nature Conservancy) for more details on how rasters were developed. </p>
Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Intermediary Result
<p>The intermediary result of the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".</p>
Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Category Confusion Matrix
<p>Resulting category confusion matrix for the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".</p>
Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Result
<p>The result for the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".</p>
Datasets for manuscript - Dirichlet diffusion score model for biological sequence generation.
<p>This repository holds the trained Dirichlet Diffusion Score models for various datasets.</p> <p><strong>best_models.tar.gz</strong></p> <p>It also contains all input data required to train your own models with scripts provided via <a href="https://github.com/jzhoulab/ddsm">github repository</a>.</p> <p><strong>data.tar.gz</strong></p> <p>This archive contains the following folders: </p> <ul> <li><strong>satnet_sudoku </strong>contains dataset with sudoku examples which we used for evaluation of sudoku model.</li> <li><strong>promoter_design</strong> contains dataset used for training promoter design model as well as Sei model weights. Please, read provided readme file before using it for training scripts. </li> </ul>
Polygenic risk scores validated in patient-derived cells stratify for mitochondrial subtypes of Parkinson's disease
<p><strong>Background</strong> Parkinson’s disease (PD) is the fastest growing neurodegenerative disorder, with affected individuals expected to double during the next 20 years. This raises the urgent need to better understand the genetic architecture and downstream cellular alterations underlying PD pathogenesis, in order to identify more focused therapeutic targets. While only ∼10% of PD cases can be clearly attributed to monogenic causes, there is mounting evidence that additional genetic factors could play a role in idiopathic PD (iPD). In particular, common variants with low to moderate effect size in multiple genes regulating key neuroprotective activities may act as risk factors for PD. In light of the well-established involvement of mitochondrial dysfunction in PD, we hypothesized that a fraction of iPD cases may harbour a pathogenic combination of common variants in nuclear-encoded mitochondrial genes, ultimately resulting in neurodegeneration.</p> <p><strong>Methods</strong> to capture this mitochondria-related “missing heritability”, we leveraged on existing data from previous genome-wide association studies (GWAS) – i.e., the large PD GWAS from Nalls and colleagues. We then used computational approaches based on mitochondria-specific polygenic risk scores (mitoPRSs) for imputing the genotype data obtained from different iPD case-control datasets worldwide, including the Luxembourg Parkinson’s Study (412 iPD patients and 576 healthy controls) and the COURAGE-PD cohorts (7270 iPD cases and 6819 healthy controls).</p> <p><strong>Results</strong> applying this approach to gene sets controlling mitochondrial pathways potentially relevant for neurodegeneration in PD, we demonstrated that common variants in genes regulating <em>Oxidative Phosphorylation (OXPHOS</em>-PRS<em>)</em> were significantly associated with a higher PD risk both in the Luxembourg Parkinson’s Study (odds ratio, OR=1.31[1.14-1.50], <em>p</em>=5.4e-04) and in COURAGE-PD (OR=1.23[1.18-1.27], <em>p</em>=1.5e-29). Functional analyses in primary skin fibroblasts and in the corresponding induced pluripotent stem cells-derived neuronal progenitor cells from Luxembourg Parkinson’s Study iPD patients stratified according to the <em>OXPHOS</em>-PRS, revealed significant differences in mitochondrial respiration between high and low risk groups (<em>p</em> < 0.05). Finally, we also demonstrated that iPD patients with high <em>OXPHOS</em>-PRS have a significantly earlier age at disease onset compared to low-risk patients.</p> <p><strong>Conclusions</strong> our findings suggest that OXPHOS-PRS may represent a promising strategy to stratify iPD patients into pathogenic subgroups – in which the underlying neurodegeneration is due to a genetically defined mitochondrial burden – potentially eligible for future, more tailored mitochondrially targeted treatments.</p>
PCA scores from contemporary Egyptian and Old Kingdom Egypt sample used for testing method by Musilová et al.(2016)
<p>Presented datasets consist of separate <strong>.csv</strong> files, that contain PCA scores and information about sex and population affinity. Each sample (Old Kingdom, contemporary Egypt, pooled sample etc.) has two files with PCA scores, one for shape and for form (shape + size together) as well as separate .csv file with information about sex/population. PCA scores were obtained after principal component analysis was applied to each dataset, that consisted of 3D models of skulls. PCA scores together with information about sex/population were used for training SVM for classification of sex and population. Details about samples bellow.</p> <p>The contemporary Egypt sample consists 96 CT scans, 49 males and 47 females, 3D models were obtained from DICOM data using Avizo. The Old Kingdom period sample consists of 54 3D models of skulls of individuals from Abusir and Giza, specifically 32 males and 22 females. 3D data from both samples are stored at the Laboratory of 3D Imaging and Analytical Methods, Department of Anthropology and Human Genetics, Faculty of Science, Charles university.</p> <p>Presented datasets were assembled and used as a part of study focused on testing the reliability of sex estimation method developed by Musilová et al.(2016) on non-European population. The datasets are made publicly available to enable reproducibility of the aforementioned work and to ensure data sharing and engagment for other studies focused on sex estimation using skull.</p>
Study Dataset: Shedding Light on CVSS Scoring Inconsistencies: A User- Centric Study on Evaluating Widespread Security Vulnerabilities
<p>This record contains the <strong>study datasets, descriptive results and questionnaires</strong> from the paper "Shedding Light on CVSS Scoring Inconsistencies: A User-Centric Study on Evaluating Widespread Security Vulnerabilities" by Julia Wunder, Andreas Kurtz, Christian Eichenmüller, Freya Gassmann and Zinaida Benenson to appear in Proceedings of the 45th IEEE Symposium on Security and Privacy (2024).</p> <p>The pseudonymous <strong>datasets</strong> contain data from the online surveys (main study with 196 participants and follow-up study with 59 participants). The first row gives the question codes and questions, the following rows gives the answers from the participants (see also README.md).</p> <p>We also provide <strong>descriptive results</strong> from the online surveys as PDF and the questionnaires.</p> <p>Please refer to the README.md file and our paper for further details about the data set and study.</p>
Images of daphnids (control and exposed to NMs) over multiple generations, scored by experts as toxic or non-toxic and the resulting deepDaph predictions
<p>Background</p> <p>This study showcases a pioneering application of deep learning methodologies in ecotoxicology, aimed at facilitating hazard assessment and safer design of engineered nanomaterials (ENMs). The research hinges on a high-quality dataset comprising microscopic images of Daphnia magna exposed to various ENMs, collected systematically under controlled conditions.</p> <p>The Dataset: A Cornerstone of Nanoinformatics</p> <p>Our dataset, which will be openly accessible on Zenodo, serves as a foundational resource for the ecotoxicology community. It contains high-resolution images tagged with intricate details like malformations, tail lengths, lipid concentrations, and lipid deposit shapes. Researchers can use this exhaustive dataset to train a variety of predictive models for diverse applications.</p> <p>Methodology</p> <p>We employ two different deep learning architectures to process the dataset. These architectures automatically detect malformations and assess the impact of ENMs on D. magna by classifying various biological structures based on lipid densities.</p> <p>Results and Validation</p> <p>The developed models demonstrate high statistical validation, confirming their prediction accuracy on external D. magna images. Our dataset and the associated models not only accelerate manual procedures but also pave the way for automated, high-throughput analyses in ecotoxicology.</p> <p>Future Prospects</p> <p>The dataset holds the potential to extend investigations into predicting the impacts on future generations from parental exposures, thus reducing the time and cost of multi-generational toxicity assays.</p>
Credit scoring with class imbalance data: An out-of-sample and out-of-time perspective
<p>The raw datasets provided here are intended for use in a Data in Brief article. These comprehensive files, sourced from the Freddie Mac website, offer quarterly snapshots of mortgage loans that have been originated in the USA since 1999, along with details of their subsequent repayment behaviours. This data remains current and is updated every three months. Specifically, the loan origination data present here encompasses amortized fixed-rate mortgage loans from 1999 up to June 2022. In contrast, the performance data is presented on a monthly basis, detailing loan repayment profiles from 1999 until September 30, 2022. Both the origination and performance datasets feature a unique loan ID, which can be utilized to integrate the data on loan originations with that of loan repayments.</p>
Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir: data, forecasts, and scores
<p>This data publication contains zipped parquet from the Beaverdam Reservoir forecasting data assimilation experiments using the FLARE (Forecasting Lake And Reservoir Ecosystems) system: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations and meteorological data, forecasts.zip contains forecast parquet files generated from the BVR FLARE DA experiment workflow, and scores.zip contains forecast skill metrics required for analysis. Within the forecasts and scores folders, there are four runs that were conducted with different parameter tuning and uncertainty quantification. The "all_UC" folder includes forecasts run with process, driver, parameter, and initial condition uncertainty quantification. The "IC_off" folder includes forecasts run without initial conditions uncertainty included (i.e., only process, driver, and parameter uncertainty). The "constant_bad_pars" folder includes forecasts run with constant parameters (but daily updating of initial conditions) that were not tuned for Beaverdam Reservoir before forecasts were generated. Finally, the "tuned_bad_pars" folder includes forecasts that were run with daily updating of initial conditions and parameters, but the parameters started out at random values that were not tuned for Beaverdam Reservoir.</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.