{"id":"W7109693859","doi":"10.15468/dl.sy6nhj","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; Matching (statistics); Polygon (computer graphics); Range (aeronautics); South carolina","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":[0.0007318949,0.002556689,0.002005094,0.00588639,0.001524764,0.003966678,0.002976177,0.002772369,0.2627131],"category_scores_gemma":[0.006091156,0.0009661341,0.001688386,0.009503628,0.0004437357,0.00442346,0.003551727,0.002527894,0.3797008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001760675,"about_ca_system_score_gemma":0.002425633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01960677,"about_ca_topic_score_gemma":0.04300238,"domain_scores_codex":[0.9987185,0.0001450504,0.0001758411,0.0004450462,0.0003110323,0.0002045804],"domain_scores_gemma":[0.9976308,0.0005622901,0.0001776265,0.0005829131,0.0007378075,0.0003084828],"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":[0.0000402642,0.0000142081,0.0003336229,0.0005592399,0.00001144674,0.00002765062,0.00002179212,0.00009496535,0.0001066047,0.000424314,0.9952798,0.003086143],"study_design_scores_gemma":[0.00005049432,0.0000111359,0.0009982828,0.0001734094,0.00001133043,0.00006338017,0.00008152203,0.0002496466,0.000162178,0.001066093,0.9971141,0.00001847253],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001013996,0.0001401988,0.0001854234,0.0001117004,0.00004894328,0.00001555394,0.9938005,0.002226918,0.003369433],"genre_scores_gemma":[0.0003280559,0.0001071122,0.0005451586,0.0001216686,0.0000123748,0.00004807859,0.9966973,0.0004564163,0.00168381],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7372869,"threshold_uncertainty_score":0.8788629,"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."}}