{"id":"W3123346482","doi":"10.4236/ojf.2021.111002","title":"Calibration of a Confidence Interval for a Classification Accuracy","year":2021,"lang":"en","type":"article","venue":"Open Journal of Forestry","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Confidence interval; Calibration; Statistics; Interval (graph theory); Computer science; Tolerance interval; Medicine; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004991782,0.00005445583,0.0002412055,0.00002043312,0.00002887907,0.00004296459,0.0002866283,0.00003930501,0.00005177594],"category_scores_gemma":[0.006957425,0.00004410041,0.00007323267,0.00005510689,0.00003175304,0.0003652616,0.00007074546,0.00009564563,1.669578e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001597273,"about_ca_system_score_gemma":0.000192774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001505507,"about_ca_topic_score_gemma":0.000003355041,"domain_scores_codex":[0.9991434,0.00007495331,0.0005028941,0.00007663413,0.0001264338,0.0000757005],"domain_scores_gemma":[0.9974481,0.001300669,0.0005790999,0.0001758888,0.0004426872,0.00005358569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002586698,0.0001494614,0.00009664253,0.0001744211,0.00004899895,0.00001706884,0.0002796669,0.00003870226,0.02242979,0.9490088,0.001858823,0.025639],"study_design_scores_gemma":[0.0005703892,0.0001599332,0.0001732342,0.000244893,0.00004458726,0.0000725428,0.0004088371,0.008064047,0.02153901,0.9682617,0.0004077044,0.00005314884],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01575796,0.00004504509,0.9830026,0.00048443,0.00009925544,0.0001491834,0.00002294654,0.000001567179,0.0004370009],"genre_scores_gemma":[0.3238825,0.00001494972,0.6758751,0.00003142181,0.00004114482,0.00000550953,0.000002066753,0.000006613211,0.0001407427],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3081245,"threshold_uncertainty_score":0.8329191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3066914928073359,"score_gpt":0.5102435407290649,"score_spread":0.203552047921729,"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."}}