{"id":"W7083625340","doi":"10.15468/dl.cnjh7x","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Download; Set (abstract data type); 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":[0.001007666,0.001927605,0.001464589,0.005369848,0.0009608929,0.002528061,0.002614845,0.001811724,0.1531698],"category_scores_gemma":[0.006396789,0.0008944775,0.001179139,0.01084471,0.0004470812,0.002050062,0.002447827,0.001785901,0.1995811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00200499,"about_ca_system_score_gemma":0.003160347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04318803,"about_ca_topic_score_gemma":0.07160448,"domain_scores_codex":[0.9988239,0.0001566375,0.0001579172,0.0003769004,0.0002753583,0.0002092168],"domain_scores_gemma":[0.9971403,0.0006901111,0.0002817362,0.0006860904,0.0008513872,0.0003504237],"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":[0.00002881743,0.000008087193,0.0003259946,0.0004426465,0.00001291354,0.00001077447,0.00001630794,0.00009806876,0.00007972455,0.0003534665,0.9975051,0.001118184],"study_design_scores_gemma":[0.00007555765,0.000007468212,0.001994449,0.00018303,0.00001396524,0.00002891466,0.00005469317,0.0001274519,0.0001518358,0.0007075227,0.9966378,0.00001740689],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003113412,0.00002057853,0.0000262916,0.00002952784,0.00000910822,0.000004158848,0.9991055,0.0002336164,0.0005400456],"genre_scores_gemma":[0.0001349464,0.00003294952,0.0001419196,0.00004525869,0.000003287311,0.00003149614,0.999023,0.0001093247,0.0004778639],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8468302,"threshold_uncertainty_score":0.5124039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459848309783138,"score_gpt":0.2517226651428593,"score_spread":0.237124182045028,"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."}}