{"id":"W1988930334","doi":"10.1016/j.ast.2003.11.002","title":"Optimization of an air cushion vehicle bag and finger skirt using genetic algorithms","year":2003,"lang":"en","type":"article","venue":"Aerospace Science and Technology","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Genetic algorithm; Cushion; Engineering; Marine engineering; Coast guard; Algorithm; Structural engineering; Computer science","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":[0.0002360736,0.00008728977,0.0001203071,0.0002379628,0.0001612081,0.00001559213,0.0001324169,0.0001286812,0.000020936],"category_scores_gemma":[0.00006392146,0.00008499958,0.00001092545,0.0006877485,0.0009776944,0.0001508991,0.00005325906,0.00008238759,0.000002039632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001606087,"about_ca_system_score_gemma":0.0000533394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008141745,"about_ca_topic_score_gemma":0.00002127551,"domain_scores_codex":[0.9991595,0.00002041278,0.000120174,0.0003609416,0.00008987732,0.0002491319],"domain_scores_gemma":[0.9995252,0.00001123665,0.00006999762,0.0002464066,0.00009168619,0.00005546178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006789247,0.0008485664,0.1071483,0.00008404189,0.0000836636,0.00002413582,0.003441229,0.01527877,0.3426946,0.2260387,0.000122976,0.3041672],"study_design_scores_gemma":[0.008725061,0.005668082,0.484937,0.0001609255,0.0002466106,0.0006500413,0.02561133,0.3466101,0.08847837,0.03153566,0.004482238,0.00289455],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953404,0.0004838244,0.002784393,0.0003475502,0.000134613,0.0001213938,0.000001255434,0.00003564674,0.0007508905],"genre_scores_gemma":[0.9713618,0.00007787051,0.02842628,0.00007131013,0.000005099928,0.000005916601,4.700003e-7,0.000008420317,0.00004287548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3777887,"threshold_uncertainty_score":0.3602356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01045374796431505,"score_gpt":0.2768789231324324,"score_spread":0.2664251751681174,"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."}}