{"id":"W2168226975","doi":"10.1016/j.apergo.2004.01.007","title":"Automobile seat comfort prediction: statistical model vs. artificial neural network","year":2004,"lang":"en","type":"article","venue":"Applied Ergonomics","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Artificial neural network; Computer science; Artificial intelligence; Engineering; Machine learning; Simulation","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001889201,0.0002957349,0.000340848,0.00005834672,0.0002278999,0.00006158472,0.000272101,0.0002359153,0.0003104042],"category_scores_gemma":[0.000004399996,0.0003281242,0.0001259508,0.0001299939,0.0001882096,0.00007087138,0.00009981747,0.0003513627,0.0004977356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001740418,"about_ca_system_score_gemma":0.0001063993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001099931,"about_ca_topic_score_gemma":0.0001533399,"domain_scores_codex":[0.9980542,0.00001915058,0.0005160429,0.0006055484,0.0001102451,0.0006948193],"domain_scores_gemma":[0.9990731,0.00005710962,0.0001086781,0.000521449,0.00002029819,0.0002193344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004544684,0.0001576446,0.0002033447,0.000007213298,0.0000682279,0.000003378007,0.0002163114,0.4416454,0.00004071548,0.5428413,0.00544593,0.008916007],"study_design_scores_gemma":[0.009479471,0.00107789,0.1214757,0.0000308343,0.0004722563,0.00006158061,0.001244603,0.3947876,0.0001274412,0.4290687,0.03925329,0.002920617],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8686796,0.00008773601,0.06484533,0.000274111,0.002100508,0.0008171325,0.0002976653,0.0003910343,0.06250685],"genre_scores_gemma":[0.9920413,0.000024315,0.005421176,0.0009845431,0.0006450044,0.0002326734,0.0003148122,0.00007723657,0.0002588607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1233618,"threshold_uncertainty_score":0.9999171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01638534941769213,"score_gpt":0.266875180844563,"score_spread":0.2504898314268709,"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."}}