{"id":"W6943691927","doi":"10.15468/dl.r7hjgr","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":"Download; Matching (statistics); Range (aeronautics); Real world data; Set (abstract data type)","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":[0.001147988,0.001941947,0.001678092,0.005279273,0.001051956,0.002930107,0.002987402,0.002027771,0.1813025],"category_scores_gemma":[0.006842711,0.001019043,0.001153013,0.01054498,0.0004694285,0.002427955,0.00274119,0.002094431,0.2404971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001616204,"about_ca_system_score_gemma":0.00248718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02101596,"about_ca_topic_score_gemma":0.03376013,"domain_scores_codex":[0.998841,0.0001555067,0.0001555556,0.000401367,0.0002584247,0.0001882466],"domain_scores_gemma":[0.99722,0.000819122,0.0002632611,0.000718634,0.0006632171,0.0003157242],"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":[0.00002677047,0.000009912986,0.0003383373,0.0005339665,0.0000149397,0.00001431333,0.00002427169,0.0001107517,0.0001076399,0.0003998297,0.9971429,0.001276556],"study_design_scores_gemma":[0.00006779303,0.000006618179,0.001554663,0.0001911019,0.00001430278,0.00003408958,0.00006976042,0.0001240261,0.0001680741,0.0007697963,0.9969828,0.00001694582],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003184985,0.00002230782,0.00004358971,0.00003219423,0.0000107562,0.0000046407,0.998923,0.000328633,0.0006030616],"genre_scores_gemma":[0.000142346,0.00003208336,0.0001923906,0.00004330343,0.000003241766,0.00004087117,0.998916,0.0001689631,0.0004607734],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8186975,"threshold_uncertainty_score":0.6065174,"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."}}