{"id":"W4408897751","doi":"10.1109/rams48127.2025.10935169","title":"Vehicle Event Condition Monitoring Reliability in Mass Transit Fleets Using A Simplified Covariate Non-Honogeneous Poisson Proces Model","year":2025,"lang":"en","type":"article","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Covariate; Poisson distribution; Reliability (semiconductor); Transit (satellite); Computer science; Event (particle physics); Reliability engineering; Statistics; Transport engineering; Mathematics; Engineering; Public transport; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.001313632,0.0005727457,0.0006123491,0.0005236546,0.0003279427,0.0008915259,0.001107266,0.0007037343,0.002107039],"category_scores_gemma":[0.003234256,0.0004008082,0.001016323,0.000519542,0.0005965479,0.000950164,0.0006390653,0.0008529469,0.0002248962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109394,"about_ca_system_score_gemma":0.0006436479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02660486,"about_ca_topic_score_gemma":0.011865,"domain_scores_codex":[0.999558,0.0001567938,0.0000178256,0.0001208479,0.00007479976,0.00007160235],"domain_scores_gemma":[0.9984724,0.0009415744,0.0002471044,0.000109159,0.0001650022,0.00006479301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003085019,0.00001275583,0.002223445,0.000008071097,0.00001344577,0.00006155649,0.00002245639,0.9914967,0.0003427708,0.004008653,0.0001129725,0.001666351],"study_design_scores_gemma":[0.000001316702,0.000006627368,0.0003780838,6.538976e-7,0.000002704423,0.000005837927,0.000004027065,0.9988766,0.00003912317,0.0006410291,0.0000418281,0.000002045309],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4021041,0.0002654782,0.5925801,0.0005022296,0.00004619976,0.00007856731,0.0004659056,0.0003034977,0.003653977],"genre_scores_gemma":[0.9902465,0.0001104627,0.006184476,0.00001886522,0.00002475509,0.00003418598,0.0001560374,0.00001823155,0.003206395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02660486,"threshold_uncertainty_score":0.05290002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08736893397331429,"score_gpt":0.4158896729496514,"score_spread":0.3285207389763371,"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."}}