{"id":"W6943350249","doi":"10.15468/dl.t5krmn","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":"Matching (statistics); Download; Alien; Range (aeronautics); 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":[0.0009101974,0.002078135,0.001570877,0.005030215,0.0009659579,0.0024884,0.002594465,0.001927953,0.1670626],"category_scores_gemma":[0.006212216,0.0009075108,0.001213331,0.009930402,0.0004333594,0.002165866,0.002508072,0.00178929,0.2161967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001506515,"about_ca_system_score_gemma":0.002270338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02166728,"about_ca_topic_score_gemma":0.03402648,"domain_scores_codex":[0.9989813,0.0001372616,0.000129862,0.0003671669,0.0002134919,0.0001709217],"domain_scores_gemma":[0.9975425,0.0007365949,0.0002403342,0.0006176112,0.0005905716,0.0002724772],"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":[0.00003309198,0.00001118375,0.0004118106,0.0005852926,0.00001522942,0.00001551179,0.00002301792,0.0001410864,0.0001213441,0.0003649943,0.9967607,0.001516695],"study_design_scores_gemma":[0.00007998107,0.00001053604,0.001914849,0.000199091,0.00001596173,0.00003788534,0.00006977077,0.0001669771,0.0001903735,0.0008028515,0.9964929,0.00001886314],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004296313,0.00002659003,0.00003951473,0.00003363337,0.00001161688,0.000005012875,0.9988675,0.0003776562,0.0005955552],"genre_scores_gemma":[0.0001672771,0.00003609374,0.0001960939,0.0000471756,0.000003671257,0.00004273743,0.9988791,0.0001553371,0.0004724694],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8329374,"threshold_uncertainty_score":0.5588802,"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."}}