{"id":"W2147049291","doi":"10.1109/icmla.2007.59","title":"Model evaluation for prognostics: estimating cost saving for the end users","year":2007,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Prognostics; Computer science; Train; Reliability engineering; Risk analysis (engineering); Engineering; Data mining","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":[0.003221219,0.001341065,0.001069634,0.001606585,0.0003496464,0.001318936,0.0009195515,0.001174314,0.001915032],"category_scores_gemma":[0.0146817,0.0003759628,0.0006817144,0.00123134,0.0004033369,0.002070526,0.0008016466,0.0009122134,0.0002000245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001534439,"about_ca_system_score_gemma":0.001269111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003268471,"about_ca_topic_score_gemma":0.001965609,"domain_scores_codex":[0.9984475,0.000924487,0.00005842093,0.0001001041,0.0004022569,0.00006721387],"domain_scores_gemma":[0.9934094,0.005262013,0.0003680962,0.0003953301,0.0004878557,0.00007735631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003412316,0.0001202774,0.006411301,0.0002671513,0.0001330408,0.00008750541,0.00005583973,0.8470251,0.001566054,0.01350449,0.00163525,0.1288527],"study_design_scores_gemma":[0.0000135505,0.0001110101,0.0009205852,0.00002735647,0.00003176394,0.00004279755,0.00002537079,0.9906702,0.001293869,0.006121309,0.000729785,0.00001244509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1091821,0.001904672,0.882404,0.0009756414,0.00008249055,0.0001952491,0.000562823,0.0005704738,0.004122614],"genre_scores_gemma":[0.8171628,0.001246342,0.1794116,0.00007754232,0.00007062625,0.000292344,0.0005638911,0.00008228941,0.001092553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003268471,"threshold_uncertainty_score":0.0170356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04532904582113712,"score_gpt":0.298611709316665,"score_spread":0.2532826634955279,"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."}}