{"id":"W1948757686","doi":"","title":"Craftsmanship at Intier Automotive: Increasing product quality through improved acoustical engineering","year":2001,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Magna International (Canada)","funders":"","keywords":"Automotive industry; Interfacing; Anechoic chamber; Manufacturing engineering; Engineering; Quality (philosophy); Focus (optics); Center (category theory); Product (mathematics); Automotive engineering; Computer science; Telecommunications; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002229089,0.0002709827,0.0002367239,0.0001333371,0.0001634726,0.00009176749,0.0001866135,0.000161067,0.0001874862],"category_scores_gemma":[0.0003966888,0.0003041788,0.00004778017,0.0002521159,0.00004044916,0.0001885379,0.00003397976,0.0003022538,0.00003327839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007749216,"about_ca_system_score_gemma":0.0001182712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003921708,"about_ca_topic_score_gemma":0.001843021,"domain_scores_codex":[0.9985631,0.00002085332,0.0003106619,0.0002955743,0.0001545812,0.0006552197],"domain_scores_gemma":[0.9990702,0.00006885736,0.00003369422,0.0003218673,0.0001108818,0.0003945308],"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":[0.00001480249,0.00001346519,0.001426395,0.0003672983,0.00005437126,0.00005466646,0.0004652628,0.9750918,0.01809418,0.0001157107,0.002084285,0.00221774],"study_design_scores_gemma":[0.0003211505,0.00001573439,0.05504372,0.00005982623,0.0000695604,0.00006218757,0.00007703431,0.9301011,0.001963206,0.00006588472,0.01150719,0.0007134347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7108103,0.000276031,0.2827258,0.0002260019,0.001077965,0.000322964,0.00006607749,0.0007375907,0.00375734],"genre_scores_gemma":[0.9778987,0.0001180879,0.02094208,0.0001765909,0.000350006,0.00001512599,0.0000484362,0.00008589721,0.0003650895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2670884,"threshold_uncertainty_score":0.9999411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01516035329867055,"score_gpt":0.2285168129443809,"score_spread":0.2133564596457104,"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."}}