{"id":"W2030297173","doi":"10.1115/gt2010-22213","title":"Laplace Correction of Confusion Matrices to Produce Statistically Representative Confidence Intervals","year":2010,"lang":"en","type":"article","venue":"Volume 3: Controls, Diagnostics and Instrumentation; Cycle Innovations; Marine","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Confidence interval; Laplace distribution; Laplace transform; Statistics; Tolerance interval; Matrix (chemical analysis); Mathematics; Coverage probability; Confidence distribution; Sample size determination; Applied mathematics; Algorithm; Mathematical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02628788,0.001691994,0.001265081,0.004534459,0.001096052,0.003063427,0.002079008,0.001397931,0.006321789],"category_scores_gemma":[0.2314818,0.0007120717,0.001458554,0.002035124,0.001580346,0.002424688,0.002643947,0.003958452,0.001570711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001369291,"about_ca_system_score_gemma":0.002089391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001901381,"about_ca_topic_score_gemma":0.001871869,"domain_scores_codex":[0.983918,0.007746183,0.001196146,0.001856404,0.004800558,0.0004827211],"domain_scores_gemma":[0.7827073,0.1737971,0.006726198,0.01341519,0.02263073,0.0007234028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009297176,0.0002673178,0.007726776,0.0008131832,0.0003928974,0.0006124581,0.001453549,0.2518643,0.01634878,0.1012805,0.007739328,0.6105713],"study_design_scores_gemma":[0.00008712971,0.0004046554,0.003772664,0.0002145203,0.00007504191,0.000571047,0.00022174,0.8916363,0.03157662,0.06458519,0.006708917,0.0001461563],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006458495,0.0001061252,0.9913256,0.00007847536,0.00006527045,0.0001685576,0.00008219442,0.0008939601,0.0008212649],"genre_scores_gemma":[0.1615926,0.0001408126,0.8355275,0.0001375733,0.00008794262,0.0005206499,0.0004758715,0.0003619476,0.001155009],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02628788,"threshold_uncertainty_score":0.1390253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005388543905552805,"score_gpt":0.2412114300270104,"score_spread":0.2358228861214576,"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."}}