{"id":"W2229638205","doi":"10.4271/2001-01-0843","title":"A Case Study of a Hidden Airbag Door Deployment, with an SMA IP, Using FEA and Data Acquisition for Design Optimization","year":2001,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Architecture and Computational Design","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Chemicals (Canada)","funders":"","keywords":"Airbag; Computer science; Software deployment; SMA*; Finite element method; Embedded system; Computer hardware; Engineering; Software engineering; Structural engineering","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":[0.0004252016,0.000462362,0.00053759,0.0001906046,0.0002761456,0.00007268981,0.0004978657,0.0002611554,0.00003484798],"category_scores_gemma":[0.00007837029,0.0003930463,0.000068089,0.0004916657,0.0002187467,0.0005948896,0.0001920095,0.0003285243,0.000001131106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042022,"about_ca_system_score_gemma":0.00005087407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005368644,"about_ca_topic_score_gemma":0.01346314,"domain_scores_codex":[0.9976206,0.0001332025,0.0006087129,0.0007817729,0.0004338504,0.0004218889],"domain_scores_gemma":[0.998241,0.0003807055,0.0001276496,0.0009587788,0.00009089134,0.000200954],"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":[0.002591894,0.001437746,0.0002666406,0.0001653361,0.0002975148,0.001216032,0.0004287616,0.3057605,0.6634386,0.0005563961,0.0003599016,0.02348061],"study_design_scores_gemma":[0.01614973,0.04748294,0.8700913,0.001172029,0.002540087,0.03091065,0.00522577,0.01204593,0.0003583912,0.006769812,0.001942388,0.005310955],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804003,0.000180174,0.0149017,0.0001586802,0.00005485104,0.002519116,0.00007226035,0.001394269,0.0003186908],"genre_scores_gemma":[0.8696674,0.00004569309,0.129673,0.0001490036,0.00007340915,0.0001935788,0.00008181826,0.0001080942,0.000008002019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8698247,"threshold_uncertainty_score":0.9998521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04171656545175847,"score_gpt":0.2807014225460769,"score_spread":0.2389848570943184,"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."}}