{"id":"W2084419136","doi":"10.4271/2014-01-0943","title":"A Technique to Predict Thermal Buckling in Automotive Body Panels by Coupling Heat Transfer and Structural Analysis","year":2014,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Engineering Applied Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Chrysler (Canada)","funders":"","keywords":"Heat transfer; Automotive industry; Buckling; Coupling (piping); Thermal; Materials science; Thermal analysis; Structural engineering; Mechanics; Composite material; Engineering; Thermodynamics; Physics; Aerospace 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":[0.0002147208,0.0006762452,0.0003932543,0.0006681026,0.0005147537,0.0003581182,0.000678765,0.0008795769,0.001595704],"category_scores_gemma":[0.0006296926,0.0005222447,0.0006335757,0.0004187608,0.0002716025,0.000540243,0.0003650448,0.0007206883,0.0006398167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000341761,"about_ca_system_score_gemma":0.0004871138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003453594,"about_ca_topic_score_gemma":0.003925168,"domain_scores_codex":[0.9999206,0.00001029318,0.00000307339,0.00001294642,0.0000423868,0.00001057321],"domain_scores_gemma":[0.9998143,0.00007722982,0.00001860346,0.00003119435,0.00004861296,0.00001001805],"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":[0.00005765197,0.0001328101,0.002417036,0.00008230125,0.00003730785,0.00008490057,0.00008362951,0.8362308,0.09845317,0.002186954,0.0005234579,0.05971006],"study_design_scores_gemma":[0.0000028761,0.00002665297,0.0005680248,0.00000316531,0.000005515315,0.00001635277,0.000004984349,0.9913024,0.007557679,0.0002923059,0.0002163005,0.000003843883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1621118,0.0002286065,0.8281919,0.00008345297,0.00005004707,0.0001249201,0.0001737595,0.002151421,0.006884172],"genre_scores_gemma":[0.91335,0.0001604484,0.08328644,0.00003030157,0.00001969434,0.0001495551,0.0001289746,0.0002233508,0.00265125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003453594,"threshold_uncertainty_score":0.006866932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00601547668146892,"score_gpt":0.2331607696150864,"score_spread":0.2271452929336175,"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."}}