{"id":"W6887347315","doi":"10.15468/dl.zzd74v","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":"Matching (statistics); Range (aeronautics); Download; Set (abstract data type); 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":[0.000889623,0.001989018,0.001588015,0.004923487,0.0009763635,0.002564099,0.002704481,0.001949206,0.1660292],"category_scores_gemma":[0.005443641,0.0009524807,0.001135688,0.009893905,0.0004200476,0.002325063,0.002511306,0.001905664,0.2272552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001553792,"about_ca_system_score_gemma":0.002256855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01996091,"about_ca_topic_score_gemma":0.03468345,"domain_scores_codex":[0.9989881,0.0001328368,0.0001293998,0.0003615164,0.0002174883,0.0001706149],"domain_scores_gemma":[0.9976717,0.0006147083,0.0002293383,0.0006006048,0.0006145341,0.0002691438],"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":[0.00003224757,0.00001144548,0.0003775133,0.000572323,0.00001428411,0.00001401085,0.00002151801,0.000116699,0.0001362006,0.0003984504,0.9968312,0.001474013],"study_design_scores_gemma":[0.00006613509,0.000008208441,0.001700783,0.0001757667,0.0000135353,0.00003215789,0.00005538144,0.0001166697,0.0001839981,0.000724073,0.9969061,0.00001721365],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003808641,0.00002562261,0.00003824365,0.00002932413,0.00001063318,0.000004556936,0.998897,0.0003074968,0.0006490527],"genre_scores_gemma":[0.0001455663,0.00003412113,0.0001837497,0.00004549898,0.00000336663,0.00003942219,0.998889,0.000136981,0.0005223013],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8339708,"threshold_uncertainty_score":0.5554231,"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."}}