{"id":"W6905693306","doi":"10.15468/dl.nv9juv","title":"GBIF Occurrence Download","year":2017,"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); Range (aeronautics); Set (abstract data type); Order (exchange); Sequence (biology)","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":[0.001018005,0.00237999,0.001682201,0.007235839,0.0009337722,0.002664081,0.002774661,0.001956553,0.1490462],"category_scores_gemma":[0.006160178,0.0009569866,0.001253407,0.01396941,0.0005357093,0.002444967,0.003020515,0.001851081,0.2004652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001892439,"about_ca_system_score_gemma":0.003328062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03346685,"about_ca_topic_score_gemma":0.04741714,"domain_scores_codex":[0.9988496,0.0001148145,0.000155546,0.0003734735,0.0002825956,0.0002239439],"domain_scores_gemma":[0.9968906,0.0006975321,0.0003254069,0.0007734249,0.0009502059,0.0003628269],"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":[0.0000337041,0.00001014808,0.0004349774,0.0004935908,0.00001444991,0.00001736451,0.00002724796,0.0001241712,0.0001141573,0.0004255158,0.9969022,0.001402505],"study_design_scores_gemma":[0.00008107883,0.000009300127,0.002518832,0.0001999198,0.00001408364,0.00003901496,0.00008888546,0.0001447381,0.0001971295,0.0007550445,0.9959316,0.00002038119],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004701181,0.00002419209,0.00003241751,0.00002770559,0.00001295577,0.000004551805,0.9989041,0.0003745434,0.0005725996],"genre_scores_gemma":[0.0001460784,0.00003108474,0.0001428903,0.00002916821,0.000003540486,0.00002614419,0.9991405,0.000130766,0.0003497833],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8509538,"threshold_uncertainty_score":0.4986094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02369895394788986,"score_gpt":0.2538386121692184,"score_spread":0.2301396582213285,"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."}}