{"id":"W6905880149","doi":"10.15468/dl.wtzpb5","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Range (aeronautics); State (computer science); Identification (biology)","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":[0.0009166853,0.002090111,0.001577057,0.005103696,0.001021992,0.002580711,0.002926675,0.002030589,0.1606675],"category_scores_gemma":[0.005794445,0.0009681166,0.001200139,0.01009262,0.0004626159,0.002335908,0.002573688,0.002017723,0.2231392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001531642,"about_ca_system_score_gemma":0.002325752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02009508,"about_ca_topic_score_gemma":0.03505188,"domain_scores_codex":[0.9989188,0.0001482729,0.0001338716,0.0003966304,0.000227495,0.0001750711],"domain_scores_gemma":[0.9975612,0.0006792652,0.0002280043,0.0006477102,0.0005995727,0.0002843061],"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":[0.00003046019,0.00001147838,0.000360263,0.0004904834,0.00001361673,0.00001387534,0.00002026041,0.0001216439,0.0001091842,0.0003620963,0.9970698,0.001396893],"study_design_scores_gemma":[0.00007246059,0.000009160607,0.001683726,0.0001700765,0.00001358169,0.00003640519,0.00006431394,0.0001457267,0.0001776129,0.0008145425,0.9967944,0.00001796549],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004464859,0.00002757943,0.00004162806,0.00003346201,0.00001242917,0.000004834208,0.9988073,0.0003630298,0.000665093],"genre_scores_gemma":[0.0001502993,0.00003254659,0.0001909847,0.00004432689,0.000003473117,0.00003924525,0.9989032,0.0001439378,0.0004920492],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8393325,"threshold_uncertainty_score":0.5374862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}