{"id":"W2231702026","doi":"10.6084/m9.figshare.1487715.v1","title":"Hybomitra arpadi (Diptera: Tabanidae) dataset","year":2015,"lang":"en","type":"article","venue":"Figshare","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Artificial intelligence; Computer science; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003883061,0.0005963473,0.0005956111,0.001164474,0.0005153656,0.0007689825,0.001039192,0.0005679752,0.0569387],"category_scores_gemma":[0.001446528,0.0002929913,0.0005822007,0.001670564,0.0001519097,0.0005234845,0.0008424445,0.0006764228,0.04464811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006234004,"about_ca_system_score_gemma":0.0008282303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02325057,"about_ca_topic_score_gemma":0.0431771,"domain_scores_codex":[0.9998199,0.00002462664,0.00002046166,0.00005388728,0.00004281258,0.00003831822],"domain_scores_gemma":[0.9994794,0.00007948141,0.00006657167,0.0001305522,0.0001789023,0.00006503952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001652185,0.00002676414,0.008571049,0.0005320541,0.00007265249,0.00005808503,0.00006410287,0.0004116168,0.0008192798,0.0005409096,0.9798136,0.00892466],"study_design_scores_gemma":[0.0001644905,0.00003430406,0.05194747,0.0001966158,0.0000613861,0.0001249092,0.000135345,0.0008512256,0.0008074251,0.0009560647,0.9446877,0.00003305682],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006975914,0.00006122031,0.00008701425,0.00003774578,0.00001954812,0.000009104656,0.9980785,0.0001901705,0.0008191324],"genre_scores_gemma":[0.002052849,0.00004687142,0.0003955537,0.00003227407,0.000005789479,0.00004840215,0.9966803,0.00004082736,0.0006972299],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0569387,"threshold_uncertainty_score":0.1904789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03769096378420495,"score_gpt":0.2751786323517988,"score_spread":0.2374876685675938,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}