{"id":"W6924528177","doi":"10.15468/dl.ufwzno","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); Petromyzon; Range (aeronautics); Process (computing)","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":[0.0009361253,0.001885372,0.001565027,0.005523549,0.001061621,0.003024151,0.00307862,0.00191866,0.1583294],"category_scores_gemma":[0.006591298,0.0008925888,0.001208278,0.01143197,0.0004481575,0.002549447,0.002913033,0.002150714,0.2364101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0017819,"about_ca_system_score_gemma":0.002859275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0283726,"about_ca_topic_score_gemma":0.04814801,"domain_scores_codex":[0.9989457,0.0001339751,0.0001284981,0.0003681332,0.0002458612,0.0001778852],"domain_scores_gemma":[0.9975752,0.0006473994,0.0002203094,0.0006192902,0.0006535578,0.0002842041],"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":[0.00002254563,0.000008562491,0.0003625269,0.0004927698,0.00001400006,0.00001354282,0.00002506751,0.0001011809,0.00008102062,0.0004334127,0.9970499,0.001395421],"study_design_scores_gemma":[0.00004826813,0.000005155926,0.001389193,0.0001833528,0.00001258275,0.00003065099,0.00006953501,0.0001212821,0.0001368266,0.000765035,0.9972237,0.00001433645],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003726407,0.00003465512,0.00005008827,0.00004175683,0.00001274158,0.000005116376,0.9986137,0.0004245692,0.0007800761],"genre_scores_gemma":[0.0001448729,0.0000450689,0.0001932729,0.00004422227,0.00000343969,0.0000387935,0.9987833,0.0001725002,0.0005745449],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8416706,"threshold_uncertainty_score":0.5296646,"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."}}