{"id":"W4399499524","doi":"10.1155/2024/5062203","title":"Developing a Ship Collision Risk Assessment Model with Internal and External Factors: Focused on South Korea Maritime Environment","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Foundation of Korea; National Research Foundation","keywords":"Collision; Risk assessment; Aeronautics; Marine engineering; Engineering; Transport engineering; Risk analysis (engineering); Computer science; Business; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0008621517,0.0007538372,0.0004292451,0.000858599,0.0003878523,0.001128585,0.001051861,0.0007254567,0.001093723],"category_scores_gemma":[0.001263002,0.000365517,0.0008919108,0.0007712418,0.0003314498,0.001071808,0.0008910384,0.0006281805,0.000133177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064738,"about_ca_system_score_gemma":0.001696089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.028714,"about_ca_topic_score_gemma":0.01801527,"domain_scores_codex":[0.9996397,0.0001219381,0.00001929258,0.00009619685,0.0000557757,0.00006698218],"domain_scores_gemma":[0.9995389,0.0002171153,0.00007820742,0.00001913118,0.000116622,0.00003004504],"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":[0.00002489868,0.00004800436,0.006181753,0.00002468062,0.00003011592,0.000086687,0.00007693231,0.9822711,0.0005831012,0.002154388,0.0001554527,0.008362893],"study_design_scores_gemma":[0.000001976717,0.00002086628,0.0006822372,0.000003915795,0.00001227905,0.0000145099,0.00003946984,0.9983429,0.0000895923,0.0006817718,0.0001047712,0.000005691079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4919511,0.0002381514,0.503116,0.0002756178,0.00002181899,0.0001675788,0.0002436822,0.0001324576,0.003853501],"genre_scores_gemma":[0.9637625,0.0002098094,0.03391288,0.00002675388,0.00000672437,0.000127736,0.0001614888,0.00001661941,0.001775426],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.028714,"threshold_uncertainty_score":0.05709374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088822058462637,"score_gpt":0.2370170374728136,"score_spread":0.2261288168881873,"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."}}