{"id":"W2124950976","doi":"10.1115/1.4026399","title":"Risk Models for Evaluation and Type Classification of Personal Flotation Devices","year":2014,"lang":"en","type":"article","venue":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering","topic":"Marine and Offshore Engineering Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Underwriters Laboratories; McGill University","keywords":"Computer science; Consistency (knowledge bases); Domain (mathematical analysis); Risk analysis (engineering); Systems engineering; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001945455,0.0002727733,0.0005749463,0.0003373668,0.00004060707,0.00003725686,0.0001081434,0.0001516818,0.000001331138],"category_scores_gemma":[0.0008851046,0.0002594144,0.00008877816,0.0002406824,0.00001352753,0.0002319745,0.00002308912,0.0003498635,2.355961e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001007756,"about_ca_system_score_gemma":0.00002022237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000406079,"about_ca_topic_score_gemma":0.00001877308,"domain_scores_codex":[0.9983509,0.00005268192,0.0008079193,0.0001873523,0.0003267038,0.0002744726],"domain_scores_gemma":[0.9985774,0.0006642184,0.0002228605,0.0001285897,0.0002899024,0.0001169903],"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":[0.00002751864,0.00001242259,0.0004644002,0.0005870232,0.0001185922,5.062174e-7,0.0003389724,0.9889835,0.001400515,0.002399623,0.00002890164,0.005638015],"study_design_scores_gemma":[0.001007544,0.0001647916,0.004196607,0.000438955,0.0001675349,0.00002012332,0.0001474349,0.9923516,0.0001582337,0.0001401717,0.0009595754,0.0002474195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6676282,0.003866793,0.3269323,0.00001244531,0.001135076,0.0003152507,0.00001822787,0.000074199,0.00001753271],"genre_scores_gemma":[0.9959021,0.001457925,0.002246443,0.000001342436,0.0003018592,0.00003333903,0.000007388328,0.00004727008,0.000002380383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3282738,"threshold_uncertainty_score":0.9999858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01586973356094214,"score_gpt":0.2384629641084074,"score_spread":0.2225932305474653,"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."}}