{"id":"W6905759463","doi":"10.15468/dl.vt8zhh","title":"Occurrence Download","year":2017,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Robustness (evolution); Support vector machine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008514122,0.001903374,0.001545895,0.005067631,0.0008864204,0.002478341,0.002754384,0.001872347,0.1281288],"category_scores_gemma":[0.00544409,0.0008066111,0.001131256,0.01022686,0.0004155055,0.00228047,0.002530955,0.001929699,0.1973546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001492721,"about_ca_system_score_gemma":0.002288733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02150264,"about_ca_topic_score_gemma":0.04024941,"domain_scores_codex":[0.999016,0.000131765,0.0001241959,0.0003362309,0.000230025,0.0001617195],"domain_scores_gemma":[0.9977641,0.0005789268,0.0002191881,0.0005878395,0.0005775206,0.0002723917],"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":[0.00002660386,0.00001083773,0.0004450698,0.0004950437,0.00001588562,0.0000156782,0.00002353487,0.000130274,0.0001008491,0.000382763,0.9968304,0.00152318],"study_design_scores_gemma":[0.00006156592,0.000007936346,0.002066395,0.0001883454,0.00001459088,0.0000422254,0.00008054837,0.0001759769,0.000175153,0.000800335,0.9963704,0.00001652043],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005492806,0.00003552576,0.00005261515,0.00003764835,0.00001276063,0.000005158166,0.9986984,0.0004149815,0.0006879667],"genre_scores_gemma":[0.0001667604,0.00003437656,0.0001894699,0.00003496573,0.000003188043,0.00003216176,0.999,0.0001176949,0.0004213036],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8718712,"threshold_uncertainty_score":0.4286336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387106755018206,"score_gpt":0.2528130017232275,"score_spread":0.2289419341730454,"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."}}