{"id":"W7107867867","doi":"10.15468/dl.5z2pmt","title":"Occurrence Download","year":2025,"lang":"","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Ornithology; Biodiversity; Natural history; Matching (statistics); Natural (archaeology); Range (aeronautics)","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":[0.001120619,0.002270074,0.001757232,0.005783143,0.001058053,0.002910809,0.002960052,0.002226815,0.1904768],"category_scores_gemma":[0.008135798,0.001043241,0.001364239,0.009744585,0.0004829351,0.002930203,0.003046298,0.002091486,0.2441462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001735559,"about_ca_system_score_gemma":0.002347723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02167509,"about_ca_topic_score_gemma":0.032941,"domain_scores_codex":[0.9987834,0.0001532513,0.0001607189,0.0004407189,0.0002639844,0.0001978823],"domain_scores_gemma":[0.9969319,0.0009335848,0.000265452,0.0007975906,0.0007164626,0.0003549163],"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":[0.00003409064,0.00001156709,0.0003699169,0.0005698526,0.00001546474,0.00001521926,0.00002494393,0.0001138588,0.0001030036,0.0003111699,0.9969995,0.001431423],"study_design_scores_gemma":[0.00009824663,0.00001150007,0.00218683,0.0002500029,0.00001747707,0.00004653518,0.00009810338,0.0002224373,0.000214746,0.0008725378,0.9959605,0.00002112529],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004041244,0.00002523631,0.00004736251,0.00003594329,0.00001249726,0.000006249833,0.9987689,0.0005341016,0.0005292654],"genre_scores_gemma":[0.0001604294,0.00003063348,0.0002220344,0.00004483248,0.000003958318,0.00004978411,0.9988557,0.0002085221,0.0004240339],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8095232,"threshold_uncertainty_score":0.6372085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434536157882973,"score_gpt":0.2311093459842124,"score_spread":0.2167639844053826,"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."}}