{"id":"W6905971209","doi":"10.15468/dl.sj2ck8","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); 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":[0.0009787318,0.001924806,0.001542253,0.004600235,0.001026392,0.002616047,0.002790494,0.002068843,0.1809457],"category_scores_gemma":[0.006299007,0.0008957701,0.001250722,0.008538354,0.0004358615,0.002623496,0.002643499,0.002043258,0.2541744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001502446,"about_ca_system_score_gemma":0.002255369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02022731,"about_ca_topic_score_gemma":0.03451664,"domain_scores_codex":[0.9989977,0.0001432729,0.0001156354,0.0003634293,0.0002183225,0.0001616402],"domain_scores_gemma":[0.9974009,0.0007588204,0.0002076305,0.0006992315,0.0006482265,0.0002853098],"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":[0.00002380509,0.00001050815,0.0003139616,0.00043962,0.00001148416,0.00001284501,0.00001977383,0.00009860867,0.00008996361,0.0003046415,0.9973701,0.001304712],"study_design_scores_gemma":[0.00006533263,0.000008473869,0.001649301,0.0001898017,0.00001294336,0.00003386737,0.00007225803,0.0001580637,0.0001756797,0.0008134187,0.9968035,0.00001733328],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004106781,0.00002823645,0.00004940057,0.00004525648,0.00001456401,0.000006523515,0.9986131,0.0004733178,0.0007285292],"genre_scores_gemma":[0.0001661399,0.00003601558,0.0002239224,0.00005633487,0.000004320619,0.00005077219,0.9987067,0.0001876765,0.0005680685],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8190543,"threshold_uncertainty_score":0.6053237,"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."}}