{"id":"W6924443132","doi":"10.15468/dl.4gpkqr","title":"Occurrence Download","year":2024,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arctic; Download; Marine mammal; Mammal; Ursus maritimus; 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":[0.0009807387,0.001973118,0.00165776,0.005686958,0.0009858608,0.003017433,0.002681549,0.001963309,0.2001638],"category_scores_gemma":[0.006838403,0.0009564192,0.001284286,0.01116867,0.0004003702,0.002730476,0.002770947,0.001984851,0.2631257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001644183,"about_ca_system_score_gemma":0.002263098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01840805,"about_ca_topic_score_gemma":0.02856819,"domain_scores_codex":[0.9988157,0.0001473303,0.0001692675,0.0004222539,0.0002536326,0.0001918026],"domain_scores_gemma":[0.9973055,0.0007620939,0.0002459667,0.0006724833,0.0007113526,0.0003025927],"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":[0.00002773424,0.000009742776,0.000355964,0.0005058754,0.00001350642,0.00001305654,0.00002043533,0.0001141993,0.00008394551,0.0003432859,0.9968598,0.001652585],"study_design_scores_gemma":[0.00006913444,0.000007917973,0.001603387,0.0001916098,0.00001296824,0.00003346932,0.00007115873,0.000165955,0.0001547147,0.0007786104,0.9968947,0.00001631637],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003185958,0.00002222745,0.00004177415,0.00003364185,0.0000113392,0.000005069027,0.9989156,0.0003524414,0.0005861902],"genre_scores_gemma":[0.0001435497,0.00003628499,0.0002216751,0.00004668803,0.000004243793,0.00004467128,0.9987889,0.0001660491,0.0005478989],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7998362,"threshold_uncertainty_score":0.6696147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708767307206114,"score_gpt":0.2335971948231368,"score_spread":0.2165095217510757,"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."}}