{"id":"W4410559839","doi":"10.3390/infrastructures10050126","title":"Enhancing Railway Track Intervention Planning: Accounting for Component Interactions and Evolving Failure Risks","year":2025,"lang":"en","type":"article","venue":"Infrastructures","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Component (thermodynamics); Track (disk drive); Intervention (counseling); Risk analysis (engineering); Business; Computer science; Accounting; Psychology; Physics","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":[0.002181827,0.001049224,0.0008346153,0.00215618,0.000436024,0.00168976,0.001065776,0.0007797178,0.002184418],"category_scores_gemma":[0.008815645,0.0008251545,0.0008775573,0.00141073,0.0005399464,0.002735545,0.001614722,0.0009528215,0.0002438517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001163649,"about_ca_system_score_gemma":0.001928029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01758221,"about_ca_topic_score_gemma":0.01683081,"domain_scores_codex":[0.9991844,0.0002248006,0.00006368839,0.0002079831,0.0002503454,0.0000686502],"domain_scores_gemma":[0.9963272,0.002108553,0.0007913254,0.0003340027,0.0003475446,0.00009127503],"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":[0.00003813314,0.0000384865,0.00617619,0.00006312011,0.00004051091,0.00006169959,0.0002220705,0.9157442,0.001172565,0.005378337,0.0001941942,0.07087043],"study_design_scores_gemma":[0.000004872416,0.00003454393,0.002767786,0.00001718998,0.00002840084,0.00004268646,0.00005376524,0.9899511,0.0009159658,0.005144465,0.001019551,0.00001975142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02705305,0.00008928454,0.971163,0.00006324698,0.000007080459,0.00005056522,0.0001006796,0.0003040967,0.001168922],"genre_scores_gemma":[0.6067982,0.0002541721,0.3913398,0.00002712573,0.00002458598,0.00009436487,0.0002646936,0.0001117608,0.001085287],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01758221,"threshold_uncertainty_score":0.03495973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008482864157130047,"score_gpt":0.2652552829470778,"score_spread":0.2567724187899478,"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."}}