{"id":"W6962012833","doi":"10.15468/dl.q3t8ax","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); Data set; 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":[0.001075607,0.002046527,0.001694603,0.005281146,0.00103699,0.002675917,0.002883456,0.002078635,0.1722866],"category_scores_gemma":[0.006315816,0.0009715359,0.001166976,0.01039326,0.0004612307,0.002407597,0.00264388,0.002071233,0.2333224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001636874,"about_ca_system_score_gemma":0.002443732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02184608,"about_ca_topic_score_gemma":0.03558468,"domain_scores_codex":[0.9989273,0.0001464147,0.0001347713,0.0003757197,0.0002386003,0.000177118],"domain_scores_gemma":[0.9973856,0.0007564339,0.0002439398,0.0006716854,0.0006336289,0.0003087395],"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":[0.00002854887,0.00001073505,0.0003411996,0.0005508592,0.00001443374,0.00001431369,0.00002363848,0.000114753,0.0001134944,0.0003780559,0.9970869,0.001323045],"study_design_scores_gemma":[0.00007228889,0.000007166375,0.001662087,0.0001846879,0.00001358043,0.00003302017,0.00006776416,0.0001227148,0.0001818806,0.0007667128,0.9968709,0.00001724235],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003601618,0.00002464619,0.00004262124,0.00003142001,0.00001022885,0.000004952713,0.9988632,0.0003509776,0.0006359686],"genre_scores_gemma":[0.0001549074,0.00003233933,0.0001900757,0.00004338745,0.000003261991,0.00004294147,0.9988889,0.0001640572,0.0004801862],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8277134,"threshold_uncertainty_score":0.5763561,"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."}}