{"id":"W6887268046","doi":"10.15468/dl.x3k2z7","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; Alien; Range (aeronautics); State (computer science)","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":[0.0008572837,0.002033583,0.001444191,0.004651523,0.0009209601,0.002299216,0.002568815,0.001875769,0.1483554],"category_scores_gemma":[0.005406928,0.0008535734,0.001209871,0.009301704,0.0004273818,0.002105674,0.002407991,0.00176404,0.2056257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001409949,"about_ca_system_score_gemma":0.002219744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02045179,"about_ca_topic_score_gemma":0.03406971,"domain_scores_codex":[0.9990301,0.0001264015,0.0001236251,0.0003513168,0.000201693,0.000166861],"domain_scores_gemma":[0.9978063,0.0006037896,0.0002121195,0.0005741123,0.0005436317,0.0002601797],"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":[0.00003294836,0.00001201405,0.0004086616,0.0004912937,0.00001408547,0.00001434794,0.00002000528,0.0001318504,0.0001237217,0.0003312724,0.9969423,0.001477409],"study_design_scores_gemma":[0.00008208434,0.00001153693,0.002102841,0.0001764855,0.00001544044,0.0000409473,0.00006995047,0.0001745563,0.0002144184,0.0007714917,0.9963211,0.00001925343],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005262238,0.00002677968,0.00004056307,0.00003397336,0.00001345898,0.000005198861,0.9988224,0.000378633,0.0006262606],"genre_scores_gemma":[0.0001651121,0.00003179118,0.000186726,0.00004399013,0.000003634201,0.00003818614,0.9989273,0.0001338935,0.0004694465],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8516446,"threshold_uncertainty_score":0.4962983,"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."}}