{"id":"W6906046292","doi":"10.15468/dl.wz3tke","title":"Occurrence Download","year":2023,"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; UniProt","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":[0.0009821001,0.001945492,0.001555996,0.004972875,0.001021124,0.002488535,0.002756141,0.002110721,0.1433226],"category_scores_gemma":[0.005827143,0.000888214,0.001294015,0.009453465,0.0004617678,0.00223653,0.002557826,0.002037186,0.2077466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001582442,"about_ca_system_score_gemma":0.002359168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02281709,"about_ca_topic_score_gemma":0.03740603,"domain_scores_codex":[0.9989378,0.0001473796,0.0001308182,0.0003672299,0.0002380449,0.000178642],"domain_scores_gemma":[0.9974535,0.0007380606,0.0002290799,0.0006901397,0.0006008195,0.00028833],"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":[0.00002916498,0.00001273736,0.0004180706,0.0005123859,0.00001438532,0.00001561716,0.00002509967,0.0001273185,0.0001139646,0.0003561661,0.9969257,0.001449448],"study_design_scores_gemma":[0.00007393712,0.000009751871,0.002222552,0.0002059124,0.00001502496,0.00004158388,0.00008613152,0.0001623722,0.000197608,0.0007662855,0.9962005,0.00001838649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005174047,0.00002975459,0.00004367422,0.0000400178,0.00001341913,0.000005658657,0.998804,0.0003911467,0.000620508],"genre_scores_gemma":[0.0001680768,0.00003336944,0.0001893447,0.00004497815,0.000003575318,0.00004115529,0.9989229,0.0001334821,0.0004631919],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8566774,"threshold_uncertainty_score":0.4794618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}