{"id":"W6887086052","doi":"10.15468/dl.nmumnj","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":[0.0009030944,0.002054124,0.001571916,0.0049044,0.0009696549,0.002517534,0.002656428,0.001930977,0.166395],"category_scores_gemma":[0.005865831,0.0009039812,0.001215151,0.009801895,0.0004444946,0.00218456,0.002515888,0.001860146,0.227425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001489257,"about_ca_system_score_gemma":0.002236329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02101913,"about_ca_topic_score_gemma":0.03457874,"domain_scores_codex":[0.999003,0.0001331692,0.0001240096,0.0003608904,0.000210402,0.0001686151],"domain_scores_gemma":[0.9976856,0.0006734363,0.0002278151,0.0005837532,0.000566688,0.000262812],"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":[0.00003067106,0.00001108872,0.0003934868,0.0005500063,0.00001429025,0.00001436077,0.00002198825,0.0001307431,0.0001130702,0.0003523215,0.996877,0.001491054],"study_design_scores_gemma":[0.00007444542,0.000009710009,0.00183644,0.0001917518,0.00001489967,0.0000361539,0.00006758175,0.0001549194,0.0001836434,0.0008009479,0.9966111,0.00001831083],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004270774,0.00002668176,0.00004106098,0.00003291442,0.00001205172,0.000004848603,0.9988593,0.0003697073,0.0006107735],"genre_scores_gemma":[0.0001630335,0.00003501201,0.0002000847,0.00004756563,0.000003765815,0.00004345861,0.9988426,0.0001598479,0.0005046492],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8336049,"threshold_uncertainty_score":0.5566468,"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."}}