{"id":"W4407596499","doi":"10.1016/j.ress.2025.110911","title":"A systems-theoretic approach using association rule mining and predictive Bayesian trend analysis to identify patterns in maritime accident causes","year":2025,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Canada First Research Excellence Fund; Ocean Frontier Institute; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Association rule learning; Accident (philosophy); Bayesian probability; Data mining; Computer science; Econometrics; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.004413624,0.001147001,0.001225128,0.008977356,0.000754517,0.002367273,0.001570213,0.0009560475,0.002000613],"category_scores_gemma":[0.01636451,0.0005812238,0.002126249,0.006282753,0.0009186735,0.003063648,0.001364572,0.001271202,0.0005376096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377937,"about_ca_system_score_gemma":0.002445004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007805002,"about_ca_topic_score_gemma":0.007805107,"domain_scores_codex":[0.9968396,0.001061856,0.0003330469,0.0007239626,0.0009317924,0.0001096854],"domain_scores_gemma":[0.9917813,0.005354934,0.001017508,0.0005865099,0.001168746,0.00009113672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001483768,0.0006018418,0.04979751,0.001137,0.001425223,0.0008624304,0.001446001,0.3429371,0.0035112,0.1242914,0.003233437,0.4706085],"study_design_scores_gemma":[0.00001782151,0.0001256007,0.005982384,0.000103839,0.0002135211,0.0002809585,0.0003143467,0.9216501,0.0008826361,0.06691567,0.00345477,0.0000583775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01476809,0.0004058402,0.9815353,0.000392064,0.0000475133,0.0001657678,0.0003745208,0.0003760811,0.001934798],"genre_scores_gemma":[0.3720108,0.001076646,0.6234367,0.0001795789,0.0001846387,0.000528853,0.00109286,0.00006247513,0.001427479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008977356,"threshold_uncertainty_score":0.02334172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004683114044668266,"score_gpt":0.2288358825237234,"score_spread":0.2241527684790552,"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."}}