{"id":"W4415998455","doi":"10.1016/j.oceaneng.2025.123248","title":"Maritime transit delay prediction with causal inference and machine learning","year":2025,"lang":"en","type":"article","venue":"Ocean Engineering","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Interpretability; Causal inference; Robustness (evolution); Port (circuit theory); Key (lock); Inference; Identification (biology); Predictive modelling","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007603459,0.0001363794,0.0001228528,0.0001081052,0.00005071567,0.00003897676,0.00004600428,0.00006361058,0.00003635128],"category_scores_gemma":[0.0000177959,0.0001394704,0.00001640819,0.0001952866,0.00001311841,0.0001292394,0.0000121555,0.0002832478,0.000002432728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003386709,"about_ca_system_score_gemma":0.000009127522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000996537,"about_ca_topic_score_gemma":0.000007476584,"domain_scores_codex":[0.9994866,0.000007056379,0.000134474,0.0001260883,0.00008045248,0.0001653217],"domain_scores_gemma":[0.999791,0.00004658581,0.000007445039,0.00008057125,0.00001564551,0.00005874718],"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":[0.00001492023,0.000008321484,0.01467839,0.0002677318,0.00008529292,0.00001677285,0.0001962063,0.9700211,0.001625586,0.001732728,0.0001198884,0.01123304],"study_design_scores_gemma":[0.000408579,0.00002627918,0.01396628,0.000125931,0.00002329817,0.00001627325,0.00001142407,0.9764258,0.0007320302,0.00001470847,0.008096705,0.0001527447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2153681,0.0009720612,0.769537,0.0001409835,0.0002876044,0.00024401,0.00003902022,0.001910032,0.01150122],"genre_scores_gemma":[0.9980612,0.0000898835,0.001375469,0.00001598411,0.00002532155,0.000003431824,0.00002961635,0.0000236348,0.0003754365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7826931,"threshold_uncertainty_score":0.5687438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003731485906702914,"score_gpt":0.1760302385941574,"score_spread":0.1722987526874545,"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."}}