{"id":"W6887193787","doi":"10.15468/dl.rybkn7","title":"Occurrence Download","year":2016,"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); Data collection; Vertebrate","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":[0.001023996,0.002027746,0.001602177,0.00558522,0.0008595515,0.002602211,0.002728085,0.001930563,0.1890106],"category_scores_gemma":[0.006495309,0.0009073535,0.001152176,0.01040476,0.0004126954,0.002454381,0.002904489,0.001929858,0.251361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001614558,"about_ca_system_score_gemma":0.002503239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01977864,"about_ca_topic_score_gemma":0.03453224,"domain_scores_codex":[0.9989049,0.0001432607,0.0001452458,0.0003722077,0.0002515182,0.000182769],"domain_scores_gemma":[0.9973579,0.000675071,0.0002721165,0.0006907965,0.0006578896,0.000346241],"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":[0.00002818899,0.000008863311,0.0003229141,0.0005093705,0.00001425476,0.00001161191,0.00001909032,0.0001009979,0.00009579071,0.0003399629,0.9971381,0.001410766],"study_design_scores_gemma":[0.00006965976,0.000007519654,0.001611945,0.0001875031,0.00001311197,0.00003103445,0.00005371178,0.0001166326,0.0001633347,0.0006990934,0.9970313,0.00001506961],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000324614,0.00002617136,0.00003710905,0.00003107475,0.0000104023,0.00000478027,0.9989317,0.000343255,0.0005830902],"genre_scores_gemma":[0.0001393537,0.00003474197,0.0001653515,0.00004066708,0.000003606433,0.00003610833,0.9989742,0.0001395554,0.0004664819],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8109894,"threshold_uncertainty_score":0.6323036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01734962626846364,"score_gpt":0.227796013577581,"score_spread":0.2104463873091174,"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."}}