{"id":"W6905879283","doi":"10.15468/dl.yrs2ck","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); Alien; 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":[0.0009680257,0.001993651,0.001511701,0.004828879,0.001022756,0.00253008,0.002717693,0.002150395,0.1627304],"category_scores_gemma":[0.005974165,0.0008692179,0.001258371,0.008998529,0.000458785,0.002402491,0.002592687,0.001996788,0.2339102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001525567,"about_ca_system_score_gemma":0.002256686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0211481,"about_ca_topic_score_gemma":0.03378692,"domain_scores_codex":[0.9989938,0.0001453968,0.0001228054,0.0003557118,0.0002151171,0.0001671947],"domain_scores_gemma":[0.9974449,0.0007330821,0.0002148674,0.0007033498,0.0006256197,0.0002782145],"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":[0.00002767935,0.00001189258,0.0003652857,0.0004741201,0.00001231277,0.0000149047,0.00002225265,0.000118252,0.0001044533,0.0003249879,0.9971218,0.00140216],"study_design_scores_gemma":[0.00007378606,0.000009592395,0.001888899,0.0001959784,0.00001328287,0.00003724562,0.0000841665,0.0001707102,0.000187313,0.0007627334,0.9965582,0.00001807633],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000489304,0.00002829167,0.00004647594,0.00004456038,0.00001505191,0.000006479897,0.9987116,0.0004329605,0.000665752],"genre_scores_gemma":[0.0001687202,0.00003294526,0.0002080609,0.00004929152,0.00000416112,0.00004768839,0.9988376,0.0001506776,0.0005008472],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8372696,"threshold_uncertainty_score":0.5443875,"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."}}