{"id":"W7105797177","doi":"10.48336/10","title":"A Delphi study to formalize domain knowledge on maritime collision avoidance and to inform training","year":2025,"lang":"en","type":"other","venue":"NPARC","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bridge (graph theory); Subject-matter expert; Delphi method; Collision avoidance; Delphi; Collision; Key (lock); Domain (mathematical analysis)","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":[0.04247656,0.0008211762,0.0005078894,0.003711697,0.005268034,0.002390131,0.001186269,0.001642286,0.01351571],"category_scores_gemma":[0.03396405,0.0008997018,0.0005220954,0.002613554,0.003061048,0.003214215,0.006063373,0.002345452,0.002205517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005758494,"about_ca_system_score_gemma":0.01377294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005331667,"about_ca_topic_score_gemma":0.007012237,"domain_scores_codex":[0.9770545,0.01667982,0.001416993,0.0008921257,0.001759819,0.00219672],"domain_scores_gemma":[0.9730965,0.01823378,0.000692882,0.0009566309,0.00597847,0.00104168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004788783,0.001441724,0.0070847,0.002185983,0.00002621624,0.001643939,0.7682783,0.003850508,0.009475653,0.04347721,0.01872475,0.1433321],"study_design_scores_gemma":[0.0001467218,0.001139215,0.007527879,0.001427541,0.00001854187,0.0003307476,0.8230069,0.005503219,0.00337579,0.01233554,0.145075,0.0001129091],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6915466,0.0003746985,0.09814515,0.004918438,0.0004034109,0.09292584,0.001370593,0.0001723045,0.110143],"genre_scores_gemma":[0.7588216,0.001081015,0.1186581,0.002576844,0.00006392063,0.09139968,0.0008863501,0.00008223146,0.02643024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04247656,"threshold_uncertainty_score":0.2246401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02625133234102817,"score_gpt":0.3122414414228422,"score_spread":0.285990109081814,"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."}}