{"id":"W6925072239","doi":"10.15468/dl.wxhh7g","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); Range (aeronautics); Alien; Identification (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":[0.001053326,0.001988929,0.001580421,0.004917254,0.00103529,0.00269331,0.002739458,0.002169596,0.1641103],"category_scores_gemma":[0.006651256,0.0009087178,0.001291499,0.009461126,0.0004594377,0.002454671,0.002625457,0.002020672,0.230639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001576114,"about_ca_system_score_gemma":0.002392253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02246938,"about_ca_topic_score_gemma":0.03425991,"domain_scores_codex":[0.9988956,0.0001596479,0.0001389474,0.0003899705,0.000235769,0.0001799362],"domain_scores_gemma":[0.9971619,0.0008582367,0.0002394874,0.0007446971,0.0006970966,0.0002986128],"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":[0.00002903571,0.0000122724,0.0004068373,0.0005386582,0.0000140436,0.00001508562,0.00002436159,0.000127869,0.0001052456,0.0003536223,0.996938,0.001435039],"study_design_scores_gemma":[0.00007466552,0.000009535772,0.001920735,0.0002169539,0.000014522,0.00003667621,0.00008720222,0.0001733418,0.0001834252,0.0007955303,0.9964689,0.00001861172],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004441917,0.00002768862,0.00004447283,0.00004294125,0.00001391714,0.000005964199,0.9987894,0.000410175,0.0006210486],"genre_scores_gemma":[0.0001694515,0.00003548271,0.0002056122,0.00005203999,0.000004084528,0.0000464422,0.9988398,0.0001550897,0.0004918968],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8358897,"threshold_uncertainty_score":0.5490036,"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."}}