{"id":"W6905872366","doi":"10.15468/dl.wexmzd","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); State (computer science); Alien; Range (aeronautics)","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":[0.001039146,0.001918141,0.001595176,0.0051161,0.001006989,0.002654697,0.002684979,0.002103474,0.1661411],"category_scores_gemma":[0.006619878,0.0008944137,0.001241992,0.009526673,0.0004370902,0.002397326,0.002573051,0.001954908,0.2215384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001575036,"about_ca_system_score_gemma":0.002358807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02250989,"about_ca_topic_score_gemma":0.03374485,"domain_scores_codex":[0.9989635,0.0001467436,0.0001331135,0.0003599416,0.0002252987,0.0001713625],"domain_scores_gemma":[0.9972485,0.0008672184,0.0002390851,0.0006891008,0.0006733374,0.0002827705],"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":[0.00002948873,0.00001163427,0.0004088075,0.0006115092,0.00001473899,0.00001696525,0.00002524983,0.0001277051,0.0001193254,0.0003638769,0.9967324,0.001538303],"study_design_scores_gemma":[0.00007196115,0.000009028459,0.001960973,0.0002336717,0.00001538367,0.00003827861,0.00008412164,0.0001647606,0.000183852,0.0007584354,0.9964613,0.00001824871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004290272,0.00002899128,0.00004592027,0.00004123834,0.00001277204,0.000006037253,0.9987978,0.0004111243,0.0006131991],"genre_scores_gemma":[0.0001778733,0.00003904791,0.0002186708,0.00005262308,0.000004086321,0.00005104846,0.9988117,0.0001641227,0.0004807578],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8338588,"threshold_uncertainty_score":0.5557975,"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."}}