{"id":"W6905954086","doi":"10.15468/dl.zbvnb9","title":"Occurrence Download","year":2022,"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); State (computer science); Data set","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":[0.001126994,0.001949425,0.00170824,0.005549575,0.001090372,0.002979198,0.003000252,0.002050959,0.1938881],"category_scores_gemma":[0.006887341,0.001034744,0.001185317,0.0111218,0.0004766767,0.002610391,0.002842227,0.002126897,0.2509752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001616358,"about_ca_system_score_gemma":0.002471283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0214686,"about_ca_topic_score_gemma":0.03470261,"domain_scores_codex":[0.9988157,0.0001603039,0.0001589454,0.0004107514,0.0002620089,0.0001923894],"domain_scores_gemma":[0.9971413,0.0008253711,0.0002659735,0.000751839,0.000697081,0.000318379],"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":[0.00002630307,0.000009453487,0.0003111522,0.0005232024,0.00001401068,0.00001404873,0.00002461185,0.0001003655,0.00009809624,0.0004011308,0.9972166,0.001261106],"study_design_scores_gemma":[0.00006214561,0.000006196992,0.001462898,0.0001826369,0.00001302112,0.00003287936,0.00007056676,0.0001081024,0.0001508795,0.0007557024,0.9971384,0.00001654174],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003149504,0.00002265873,0.0000462523,0.00003333691,0.00001120707,0.000004788615,0.998847,0.0003507404,0.0006525087],"genre_scores_gemma":[0.0001436133,0.00003413856,0.0001991629,0.00004522939,0.000003405332,0.00004197713,0.9988371,0.0001890039,0.0005064034],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8061119,"threshold_uncertainty_score":0.6486201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}