{"id":"W1987056569","doi":"10.1504/ijseam.2014.063882","title":"Selective maintenance considering two types of failure modes","year":2014,"lang":"en","type":"article","venue":"International Journal of Strategic Engineering Asset Management","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability engineering; Computer science; Failure rate; Preventive maintenance; Maintenance actions; Proactive maintenance; Optimal maintenance; Planned maintenance; Hazard; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002889904,0.0001310402,0.0001978181,0.0002201569,0.00001070923,0.00004254199,0.0002600217,0.00003533673,0.00001407528],"category_scores_gemma":[0.00003351922,0.0001235361,0.00008079904,0.000114666,0.00002048644,0.0002070547,0.00002790268,0.0001640251,0.000002674539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001129764,"about_ca_system_score_gemma":0.00001162688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000372991,"about_ca_topic_score_gemma":0.000002904806,"domain_scores_codex":[0.9990449,0.00001270898,0.0004175122,0.00009067067,0.0002863063,0.0001479054],"domain_scores_gemma":[0.9993642,0.00005172282,0.00013362,0.00009939096,0.000306899,0.00004418137],"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":[0.00001241334,0.0000175825,0.0000658516,0.00009044971,0.0002791823,0.00001215394,0.00004040299,0.9481041,0.002631874,0.04753068,0.0002371491,0.0009781357],"study_design_scores_gemma":[0.0009945795,0.00008404784,0.0005782871,0.0005048374,0.0000490368,0.00006734645,0.0002556494,0.9822933,0.005507264,0.007344995,0.002093052,0.0002276113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1513188,0.0001964747,0.8221474,0.0002943432,0.00150914,0.0001824172,0.000009545587,0.000131327,0.02421048],"genre_scores_gemma":[0.971213,0.0001868957,0.02841787,0.00001211412,0.0001136485,0.000003870747,0.000003043442,0.00001874739,0.00003085321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8198941,"threshold_uncertainty_score":0.5037654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008462638889081024,"score_gpt":0.2167799590998934,"score_spread":0.2083173202108124,"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."}}