{"id":"W6924414968","doi":"10.15468/dl.6772rh","title":"Occurrence Download","year":2024,"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); Polygon (computer graphics); Range (aeronautics); Code (set theory)","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":[0.0008226858,0.002328716,0.001925899,0.006072375,0.001316287,0.003740719,0.003072297,0.002172787,0.2156703],"category_scores_gemma":[0.006899381,0.0009746227,0.001667037,0.0105971,0.0003944589,0.003854263,0.0034985,0.002144924,0.3359619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165332,"about_ca_system_score_gemma":0.002467596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01876564,"about_ca_topic_score_gemma":0.03213835,"domain_scores_codex":[0.9986268,0.0001505953,0.0001875313,0.0004921428,0.0003231039,0.0002198468],"domain_scores_gemma":[0.9974265,0.000622265,0.000208684,0.0007024389,0.0007586547,0.0002816039],"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":[0.00004101761,0.00001241044,0.0004218493,0.0005758808,0.00001385584,0.00002339579,0.00002429606,0.00009816932,0.000101204,0.0003674636,0.9952223,0.003098135],"study_design_scores_gemma":[0.00004330841,0.00001004278,0.00120822,0.0001653419,0.00001219463,0.00005220461,0.00007991224,0.0002155738,0.0001714761,0.0007374119,0.997287,0.00001726114],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007827709,0.00007838353,0.000126635,0.00007855333,0.00003339535,0.000009967192,0.9962514,0.001810632,0.001532831],"genre_scores_gemma":[0.0002642553,0.00008172924,0.0004360552,0.00008556056,0.000008977155,0.00004820816,0.9975218,0.000454066,0.001099264],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7843297,"threshold_uncertainty_score":0.721489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708767307206114,"score_gpt":0.2335971948231368,"score_spread":0.2165095217510757,"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."}}