{"id":"W4224252522","doi":"10.1016/j.oceaneng.2022.111281","title":"A novel methodology to develop risk-based maintenance strategies for fishing vessels","year":2022,"lang":"en","type":"article","venue":"Ocean Engineering","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Fishing; Identification (biology); Risk analysis (engineering); Engineering; Planned maintenance; Plan (archaeology); Preventive maintenance; Reliability engineering; Business","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005329266,0.0001494409,0.0003414781,0.0004026591,0.0003287384,0.0001640317,0.0007720468,0.00003662128,0.00009158502],"category_scores_gemma":[0.007583112,0.0001341454,0.0001346736,0.001905437,0.00001488738,0.0001905052,0.0001727007,0.0002192702,0.00001041272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000862408,"about_ca_system_score_gemma":0.000169008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005287463,"about_ca_topic_score_gemma":0.00002910626,"domain_scores_codex":[0.9980242,0.0001315204,0.0004658605,0.0004541918,0.0005479826,0.0003762112],"domain_scores_gemma":[0.9959593,0.003153876,0.0001454079,0.0003900717,0.0002435535,0.0001077536],"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":[0.00003332544,0.00001315787,0.0002557246,0.000004907006,0.00002468101,0.000003497372,0.0007525393,0.9832292,0.001748606,0.00314468,0.003478855,0.00731078],"study_design_scores_gemma":[0.0006599756,0.000129817,0.005120874,0.00001369295,0.00004736353,0.00001276607,0.005726014,0.8198747,0.001024305,0.009927584,0.1569832,0.0004796608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06581337,0.00004910438,0.9317918,0.001585444,0.0003300878,0.0001484076,0.00009118862,0.00007539545,0.0001151903],"genre_scores_gemma":[0.653714,0.000003494472,0.3456255,0.0002650016,0.00005461334,0.00003475077,0.000006940361,0.00002031743,0.0002753086],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5879006,"threshold_uncertainty_score":0.9078242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1259935769690156,"score_gpt":0.3541519037175748,"score_spread":0.2281583267485592,"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."}}