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753 results for “metrics”
Radiomics metrics combined with clinical data in the surgical management of early-stage (cT1-T2 N0) of tongue squamous cell carcinomas: a preliminary study
<p>We uploaded the clinical and the hematological parameters of enrolled patients in the study "Radiomics metrics combined with clinical data in the surgical management of early-stage (cT1-T2 N0) of tongue squamous cell carcinomas: a preliminary study" accepted on Biology journal.</p> <p>Clinical and hematological parameters include: age; gender; DOI, NLR; PLR; LMR; SIRI; SII; T stage; grading; metastatic lymph nodes; perineural infiltration; vascular infiltration.</p> <p> </p>
Data from: A new composite abundance metric detects stream fish declines and community homogenization during six decades of invasions
<p><b>Aim</b>:<b> </b>We developed a new technique, utilizing species-specific counts of individuals from historical fish community samples, to examine landscape-level, spatiotemporal trends in relative abundance distributions. Abundance-based historical distribution analyses are often plagued by data comparability issues, but provide critical information about community composition trends inaccessible to those using analyses based only on species presence-absence. We established trends in native and non-native fish abundance and community homogenization, uniqueness, and diversity to help local conservation managers prioritize targets and motivate similar studies globally to support fish conservation.</p> <p><b>Location</b>: Upper and middle New River (UMNR) basin, Appalachian Mountains, USA.</p> <p><b>Methods</b>: We compiled catch data from 61 years of fish community surveys (1958-2019) and tested for community homogenization by comparing data from repeatedly sampled sites (1900s versus 2000s samples) using dispersion analyses. We measured community uniqueness (site contributions to beta diversity) and species diversity (Shannon index) at sampled streams to identify potential conservation hotspots. We then used regression analyses and Wilcoxon signed-rank tests to examine species-specific basin-wide and local abundance trends and identify species of potential conservation concern.</p> <p><b>Results</b>: Dispersion of sites in species-abundance space was significantly greater in the 1900s compared to the 2000s, indicating homogenization had occurred. Of 36 native species analyzed, 44.4% (16) showed basin-wide declines. Non-native species exhibited mixed patterns; site-level abundance increased in 2 of 15 species analyzed (13%).</p> <p><b>Main conclusions</b>: Our results indicate basin-wide community homogenization has occurred within the UMNR, but many unique and diverse communities persist. If conserved, these could help maintain regional fish diversity. We found basin-wide declines in four endemic species, as well as spread patterns of non-native and native species that were not detected by a presence-absence analysis applied within the same study area. This finding illustrates the importance of considering both species' abundance and occurrence patterns as separate dimensions of biodiversity to inform conservation planning.</p>
Dataset associated with the manuscript " Locally developed models improve the accuracy of remotely assessed metrics as a rapid tool to classify sandy beach morphodynamics"
<p>Raw dataset associated with the manuscript " Locally developed models improve the accuracy of remotely assessed metrics as a rapid tool to classify sandy beach morphodynamics"</p>
User Evaluation and Metrics Analysis of a Prototype Web-based Federated Search Engine for Art and Cultural Heritage
<p>This dataset includes the quantitative data of the usage during the evaluation phase of a prototype web-based federated search engine for art and cultural heritage related content. The metrics which resulted in the dataset were in the form of a timeline of actions taken from a user (evaluator) in the course of a single session of interaction with the platform. A total of 20 different metrics were being monitored regarding the usage of the search engine, including submitting a query, a voice query, preforming a visual search, viewing a result, viewing a visual search result, updating an avatar, editing a user profile or changing user preferences, bookmarking and removing bookmarks of results and visual search results, using text to speech of all the various elements, opening the source view of a result and clicking a concept tag. All metrics included the timestamp of the event taking place and the value of the related event (e.g. the term of a search query).</p>
Figure 3. A in Metric variation in the postcranial skeleton of ostriches, Struthio (Aves: Palaeognathae), with new data on extinct subspecies
Figure 3. A, ternary diagrams comparing intramembral (length) proportions of femur (F): tibiotarsus (TT): tarsometatarsus (TM) in the extant ratites and moas. Data for Struthio are from the present work; for other ratites from Dickison (2007). See Supporting Information (Table S19) for the ternary ratios shown in the diagram. B, ternary diagrams comparing intramembral (length) proportions of tibiotarsus (TT): tarsometatarsus (TM): pedal digit III phalanx 1 (III/1) in the extant ratites and moas. Data for Struthio are from the present work; for other ratites from Dickison (2007) for the tibiotarsus and tarsometatarsus and from Farlow et al. (2013) for the phalanx. See Supporting Information (Table S20) for the ternary ratios shown in the diagrams. C, ternary diagrams comparing intramembral (length) proportions of tarsometatarsus (TM): pedal digit III phalanx 1 (III/1): pedal digit III phalanx 2 (III/2) in the extant ratites and moas. Data for Struthio are from the present work; for other ratites from Dickison (2007) for the tarsometatarsus and from Farlow et al. (2013) for the phalanges. See Supporting Information (Table S21) for the ternary ratios shown in the diagrams. Point labels: An, Anomalopteryx didiformis; Ap, Apteryx (the mean for Apteryx australis, Apteryx mantelli and Apteryx oweni); Ca, Casuarius (the mean for Casuarius casuarius, Casuarius unappendiculatus and Casuarius bennetti); Di, Dinornis (the mean for Dinornis robustus and Dinornis novaezealandiae); Dr, Dromaius novaehollandiae; Em, Emeus crassus; Eu, Euryapteryx curtus (the mean for Euryapteryx curtus curtus and Euryapteryx curtus gravis); Me, Megalapteryx didinus; Pa, Pachyornis (the mean for Pachyornis australis, Pachyornis elephantopus and Pachyornis geranoides; Rh, Rhea (the mean for Rhea americana and Rhea pennata); Sc, Struthio camelus (the mean for Struthio camelus australis, Struthio camelus camelus and Struthio camelus massaicus); Sc+Sm, the mean for Struthio camelus and Struthio molybdophanes; Scs, Struthio camelus syriacus; Ss, Struthio camelus spatzi.
Figure 1 in Metric variation in the postcranial skeleton of ostriches, Struthio (Aves: Palaeognathae), with new data on extinct subspecies
Figure 1. Graphical representations of measurements as defined in Table 1. A, scapulocoracoid in medial view. B, sternum in dorsal view. C, synsacrum and pelvis in cranial (C1), dorsal (C2), lateral (C3) and ventral (C4) view. D, femur in medial (D1), caudal (D2), proximal (D3 and distal (D4) view. E, tibiotarsus in cranial (E1) and medial (E2) view. F, fibula in cranial (F1), lateral (F2) and caudomedial (F3) view. G, tarsometatarsus in proximal (G1), dorsal (proximal end; G2), plantar (G3) and lateral (G4) view. H, phalanx 1 in dorsal (H1), ventral (H2), lateral (H3), medial (H4) and proximal (H5) view. I, pedal digit III phalanx 2 in dorsal (I1), ventral (I2) and medial (I3) view. Anatomical abbreviations: ai, angulus ilii; al, angulus lateralis; am, angulus medialis; at, antitrochanter; c, caput femoris; cc, crista cnemialis cranialis; cn, crista cnemialis lateralis; cp,
Figure 2 in Metric variation in the postcranial skeleton of ostriches, Struthio (Aves: Palaeognathae), with new data on extinct subspecies
Figure 2. Simpson's ratio diagram comparing the lengths of scapulocoracoid (SC), humerus (H), femur (F), tibiotarsus (TT), tarsometatarsus (TM), and the first (III/1), second (III/2), and third (III/3) pedal digit III phalanges of living and extinct ostriches (Struthio), with Struthio camelus australis NHMUK 1857.2.24.10 as a reference (the black straight line at level 0). See the Supporting Information for the adopted lengths of limb segments (Table S17) and their LOG (decimal logarithmic) values (Table S18).
The Development of Russian Verse: Metrical and Rhythmic Borrowings
<p>Материалы исследовательского проекта РНФ 19-78-10132 (2019-2022), рук. Вера Полилова</p>
Binomial and toric ideal data for learning a performance metric of Buchberger's algorithm
<p>This data set consists of randomly generated binomial and toric ideals. It was used for predicting a certain complexity measure of Buchberger's algorithm for toric and binomial ideals in small number of variables. See also the corresponding code on <a href="https://github.com/Sondzus/LearningGBvaluemodel">GitHub</a> and the Involve journal paper available on <a href="https://arxiv.org/abs/2106.03676">arXiv</a>, which explains in detail the models used to generate the data. </p> <p> </p> <p><strong>From the article:</strong></p> <p>What can be (machine) learned about the performance of Buchberger's algorithm?</p> <p>Given a system of polynomials, Buchberger's algorithm computes a Gr\"obner basis of the ideal these polynomials generate using an iterative procedure based on multivariate long division. The runtime of each step of the algorithm is typically dominated by a series of polynomial additions, and the total number of these additions is a hardware-independent performance metric that is often used to evaluate and optimize various implementation choices. In this work we attempt to predict, using just the starting input, the number of polynomial additions that take place during one run of Buchberger's algorithm. Good predictions are useful for quickly estimating difficulty and understanding what features make a Gr\"obner basis computation hard. Our features and methods could also be used for value models in the reinforcement learning approach to optimize Buchberger's algorithm introduced in the second author's thesis. </p> <p>We show that a multiple linear regression model built from a set of easy-to-compute ideal generator statistics can predict the number of polynomial additions somewhat well, better than an uninformed model, and better than regression models built on some intuitive commutative algebra invariants that are more difficult to compute. We also train a simple recursive neural network that outperforms these linear models. Our work serves as a proof of concept, demonstrating that predicting the number of polynomial additions in Buchberger's algorithm is a feasible problem from the point of view of machine learning.</p>
Assessing Word Similarity Metrics for Traceability Link Recovery - Evaluation Dataset
<p>This dataset includes all data that was used for the evaluation of my bachelor's thesis:</p> <p><em>Assessing Word Similarity Metrics for Traceability Link Recovery</em></p> <p>The following files correspond to the following data sets from the evaluation:</p> <ul> <li>cc-en-300.tar.gz corresponds to fastText's cc.en.300.bin embedding</li> <li>crawl-300d-2M-subword.tar.gz corresponds to fastText's crawl-300d-2M-subword.bin embedding</li> <li>wiki-news-300d-1M-subword.tar.gz corresponds to fastText's wiki-news-300d-1M-subword.bin embedding</li> <li>wordnet.tar.gz corresponds to the WordNet 3.1 semantic network</li> <li>sewordsim.tar.gz corresponds to SEWordSimDB's vector similarity database</li> <li>glove_cc_840B_300d.tar.gz corresponds to GloVe's CC vector embedding</li> <li>glove_wikigiga_300d.tar.gz corresponds to GloVe's 300 dimensional WIGI vector embedding</li> <li>glove_wikigiga_200d.tar.gz corresponds to GloVe's 200 dimensional WIGI vector embedding</li> <li>glove_wikigiga_100d.tar.gz corresponds to GloVe's 100 dimensional WIGI vector embedding</li> <li>glove_wikigiga_50d.tar.gz corresponds to GloVe's 50 dimensional WIGI vector embedding</li> <li>glove_twitter_200d.tar.gz corresponds to GloVe's 200 dimensional TWTR vector embedding</li> <li>glove_twitter_100d.tar.gz corresponds to GloVe's 100 dimensional TWTR vector embedding</li> <li>glove_twitter_50d.tar.gz corresponds to GloVe's 50 dimensional TWTR vector embedding</li> <li>glove_twitter_25d.tar.gz corresponds to GloVe's 25 dimensional TWTR vector embedding</li> <li>eval_results.tar.gz contains the detailed evaluation results for each configuration of all measures</li> </ul> <p>The licenses of all data sets are included in their respective files.</p> <p>Some of these data sets are .sql files. To use these files to reproduce the evaluation, they need to be imported into a sqlite3 database. The version of ArDoCo used for the evaluation is only able to work with sqlite3 databases and not with sql files.</p>
Customizable Visualization of Quality Metrics for Object-Oriented Variability Implementations - Artifact
<p>This archive contains all the README files documenting the artifact (<a href="https://doi.org/10.5281/zenodo.6644449">https://doi.org/10.5281/zenodo.6644449</a>) to reproduce the results presented in the "Customizable Visualization of Quality Metrics for Object-Oriented Variability Implementations" paper presented at SPLC 2022.</p> <p>It also contains:</p> <ul> <li>the codebases of JFreeChart before and after the maintenance actions presented in section 5.2, with the corresponding diff file, as well as excerpts of the SonarQube analysis of both projects showing the information presented in table 3;</li> <li>the Excel file used to obtain the data presented in the table 2.</li> </ul> <p>An exhaustive description of the archive can be found in the README.md file.</p>
Metadata for Geospatial Mapping Tools, Indicators and Metrics for Fish Habitat in the Pacific Region
<p>Metadata on geospatial tools, indicators, metrics and scoring benchmarks useful for assessing the status of threats to freshwater fish habitat in British Columbia</p>
Eyetracking and keystroke logging metrics for measuring automaticity in translation
<p>This dataset contains the behavioural data from 35 novice translators and 30 experienced translators (65 participants in total) during their translation process. The data are specifically generated eyetracking and keystroke logging metrics for measuring automaticity in the complex activity of translation, which includes four aspects, namely, speed, degree of parallel processing, effortlessness, and the pattern of attention allocated to the source text and target text areas. The dataset is provided for the paper Automaticity in Translation: Effects of Time Pressure and Work Experience.</p>
Postural stability metrics associated to the publication: Additive manufacturing of spinal braces: evaluation of production process and postural stability in patients with scoliosis
<p>Data was collected for each condition (3D-printed brace, conventional brace, unbraced) for 60 seconds with patients in a standing posture, open eyes and both feet together.</p>
DataSet for UAV-based Untrained Small Object Detection using Distance Metric Method
<p>DataSet for UAV-based Untrained Small Object Detection using Distance Metric Method</p>
Processed data for the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data"
<p>This is the data used to reproduce the results from "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data".</p>
Scatter plots for the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data"
<p>This file contains the test-score-vs-metric plots generated by the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data".</p>
Generalization metrics for the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data"
<p>This file contains all the generalization metrics that can be used to reproduce the results of "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data".</p>
Rank correlation results for the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data"
<p>This file contains the rank correlation results from the paper "Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data".</p>
FIGURE 3. Dendrogram generated from PATN analyses using Czekanowski metric association measures the dataset comprising eight samples and 133 in Stolonochloa, a new Australian genus segregated from Panicum (Poaceae: Panicoideae: Paniceae: Boivinellinae) based on phenetic analysis of morphological data
FIGURE 3. Dendrogram generated from PATN analyses using Czekanowski metric association measures the dataset comprising eight samples and 133 morphological characters. Classification strategy set at flexible UPGMA agglomerative hierarchical fusion technique with Beta = -0.10.
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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.