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5 results for “numeric taxonomy”
FIGURE 1 in Numerical taxonomy and genus-species identification of Czekanowskiales in China based on machine learning
FIGURE 1. Distribution of Mesozoic Czekanowskiales fossils in China (Chinese basemap from the Standard Map Ser- vice, plan approval number: GS (2020) 4619).
FIGURE 4 in Numerical taxonomy and genus-species identification of Czekanowskiales in China based on machine learning
FIGURE 4. Trait importance scores for genus and species identification and heatmap of correlations between traits. (A) Importance scores for traits identified genus and species, with the solid symbols indicating key traits and the hollow symbols indicating nonkey traits; (B) proportion of importance scores for macro traits and cuticular traits identified at the genus and species; (C) heatmap of correlations between traits; serial numbers correspond to traits in Table 2.
FIGURE 5 in Numerical taxonomy and genus-species identification of Czekanowskiales in China based on machine learning
FIGURE 5. Accuracy distributions of five supervised learning algorithms and confusion matrix of the best algorithm. (A) Accuracy distribution of the five algorithms in genus-level identification (using mixed-key traits); (B) CART algorithm confusion matrix (using mixed-key traits); (C) accuracy distribution of five algorithms in genus-level identification (using only macro-key traits); (D) CART algorithm confusion matrix (using only macro-key traits); (E) accuracy distribution of five algorithms for species-level identification (using mixed-key traits); (F) LR algorithm confusion matrix (using mixed-key traits); (G) accuracy distribution of five algorithms for species-level identification (using only macro-key traits); (H) CART algorithm confusion matrix (using only macro-key traits). Genus abbreviations: Cz., Czekanowskia; Ph., Phoenicopsis; Sp., Sphenarion; So., Solenites.
FIGURE 2 in Numerical taxonomy and genus-species identification of Czekanowskiales in China based on machine learning
FIGURE 2. Fossils and schematic diagram of the leaf morphology and epidermal structure of Czekanowskia les. (A) Phoenicopsis angustifolia; (B) Czekanowskia rigida; (C) Phoenicopsis speciosa; (D) schematic diagram of the leaf morphology of Czekanowskiales, dotted line ab indicating the leaf cluster length (or lobe length), dotted line cd indicating the leaf cluster width, line ef indicating the lobe width, and angle cbd indicating the angle between bc and bd (the most lateral lobes); (E) schematic diagram of the epidermal structure of Czekanowskiales. Scale bars (A-C) equal 1 cm.
FIGURE 3 in Numerical taxonomy and genus-species identification of Czekanowskiales in China based on machine learning
FIGURE 3. Dendrogram of 35 species of the Czekanowskiales from China.
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
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DANDI Archive for NWB datasets
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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.