{"id":"W1977217436","doi":"10.1115/imece2008-66760","title":"An Efficient Crashworthiness Design Optimization Approach for Frontal Automobile Structures","year":2008,"lang":"en","type":"article","venue":"","topic":"Transportation Safety and Impact Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Crashworthiness; Nonlinear system; Finite element method; Process (computing); Computer science; Engineering design process; Design process; Engineering; Structural engineering; Work in process; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004903752,0.001124146,0.0008471358,0.0005946239,0.0004402882,0.0004655325,0.0006909269,0.0008690258,0.003336988],"category_scores_gemma":[0.0007801671,0.0004579627,0.000763984,0.0004007243,0.0003583528,0.0004117381,0.000723969,0.0007083184,0.0005260627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000385679,"about_ca_system_score_gemma":0.0008702654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002707397,"about_ca_topic_score_gemma":0.003087708,"domain_scores_codex":[0.9997825,0.0000541296,0.000009088032,0.00003144374,0.0001038188,0.00001909261],"domain_scores_gemma":[0.9998195,0.00008699563,0.00001596384,0.00001636069,0.00005484685,0.000006361589],"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":[0.00001811411,0.00004076662,0.0001847473,0.00008472001,0.00002184286,0.00004627073,0.00003882647,0.9382581,0.005711363,0.008278525,0.0006383473,0.04667843],"study_design_scores_gemma":[0.000007271147,0.00003500969,0.00007348181,0.000003872749,0.000007027164,0.00001468885,0.000006391133,0.9964929,0.0006928865,0.001703573,0.00095926,0.000003645398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003519126,0.00006166907,0.9947603,0.00002907207,0.000007190709,0.0000361182,0.00001516926,0.00007732452,0.001493911],"genre_scores_gemma":[0.3051513,0.0004463673,0.6861553,0.00009343045,0.0000649028,0.0006121554,0.0001684212,0.0002312258,0.007077049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003336988,"threshold_uncertainty_score":0.01116335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755845393411688,"score_gpt":0.2226250396046164,"score_spread":0.2050665856704995,"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."}}