{"id":"W6905921181","doi":"10.15468/dl.ugrczm","title":"Occurrence Download","year":2019,"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); Odocoileus; Data set","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":[0.0007356702,0.002005986,0.001634082,0.005967706,0.001185824,0.003295384,0.002538255,0.002317815,0.1899347],"category_scores_gemma":[0.006349605,0.0008326485,0.001504865,0.009641917,0.000353014,0.003773981,0.002866428,0.002053394,0.2938023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001593268,"about_ca_system_score_gemma":0.002282159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01808688,"about_ca_topic_score_gemma":0.0346886,"domain_scores_codex":[0.9987759,0.0001368547,0.0001783501,0.0004314178,0.0002914073,0.0001860546],"domain_scores_gemma":[0.9972317,0.0006959016,0.0002312635,0.0007095787,0.0008185384,0.000313152],"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":[0.0000453318,0.00001571499,0.0006012184,0.0007051202,0.00001650735,0.00002770081,0.00002992608,0.0001363854,0.0001358643,0.000465098,0.9937012,0.004119902],"study_design_scores_gemma":[0.00004409946,0.00001203265,0.001525702,0.0001758815,0.00001284921,0.00005496647,0.00009399839,0.0002656493,0.0001883233,0.0007756809,0.9968333,0.0000176357],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001033838,0.0001025637,0.000132239,0.00009041342,0.00003581198,0.00001135824,0.9959222,0.001611774,0.001990268],"genre_scores_gemma":[0.0003816164,0.00009506534,0.0005019567,0.0001015246,0.00001161409,0.00004496783,0.9972441,0.0003132993,0.001305928],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8100653,"threshold_uncertainty_score":0.6353949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"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."}}