{"id":"W6905695808","doi":"10.15468/dl.ojss1o","title":"Occurrence Download","year":2018,"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; Ichthyology; Matching (statistics); Range (aeronautics); Data collection","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":[0.001098159,0.001954464,0.001591592,0.006051691,0.0008922041,0.002587544,0.002810819,0.001912143,0.1729483],"category_scores_gemma":[0.006414501,0.0009013789,0.001184252,0.01074488,0.0004147279,0.002345626,0.002807912,0.001973166,0.2288076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001537881,"about_ca_system_score_gemma":0.002505345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0192643,"about_ca_topic_score_gemma":0.03340565,"domain_scores_codex":[0.9989001,0.0001478598,0.0001455603,0.0003678518,0.0002540506,0.0001846779],"domain_scores_gemma":[0.9972722,0.0007196551,0.0002688909,0.0007184633,0.0006953292,0.0003254554],"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":[0.0000280047,0.000009746521,0.0003409826,0.0005345178,0.00001614938,0.00001301304,0.00002030482,0.0001093097,0.0001037051,0.000355897,0.9969994,0.001469026],"study_design_scores_gemma":[0.00006690004,0.000007459278,0.001730741,0.0001979781,0.00001467834,0.00003283156,0.00005814261,0.0001210601,0.0001639845,0.0007706347,0.9968193,0.00001626777],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003450622,0.00002615978,0.00004157829,0.00003129578,0.00001132194,0.000005246115,0.9988917,0.0003698635,0.0005883203],"genre_scores_gemma":[0.0001409611,0.00003356822,0.0001929448,0.00004069844,0.000003688462,0.00003882198,0.9989675,0.0001528183,0.0004290165],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8270517,"threshold_uncertainty_score":0.5785697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881883250631837,"score_gpt":0.2330296220854826,"score_spread":0.2142107895791642,"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."}}