{"id":"W3205259343","doi":"10.1007/s11665-021-06312-z","title":"Statistical Analysis of Laser-Welded Blanks in Deep Drawing Process: Response Surface Modeling","year":2021,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Materials science; Surface (topology); Deep drawing; Laser; Metallurgy; Response surface methodology; Process (computing); Engineering drawing; Mechanical engineering; Composite material; Optics; Geometry; Engineering; Computer science; Machine learning; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.000772371,0.0001047205,0.0004017592,0.0002846978,0.00001364739,0.00002784711,0.00006435897,0.00006088999,0.0000330561],"category_scores_gemma":[0.0001263851,0.0001012065,0.00003513963,0.0003427179,0.000007762764,0.0002002328,0.00001262829,0.0001135669,3.249359e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003085849,"about_ca_system_score_gemma":0.00002127947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001869124,"about_ca_topic_score_gemma":0.000001110715,"domain_scores_codex":[0.9990382,0.00002941397,0.0005770103,0.00006818312,0.0001546571,0.0001325392],"domain_scores_gemma":[0.9995918,0.0001041525,0.00007645618,0.00008655653,0.00009613286,0.00004486349],"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":[0.000109554,0.000007359353,0.0008174401,0.0002922004,0.00009067562,0.00001181607,0.0002831524,0.8863657,0.1118521,0.00001221195,8.143947e-7,0.0001569802],"study_design_scores_gemma":[0.00015538,0.00003800384,0.004431879,0.0001462669,0.00007230988,0.00001677652,0.00002578119,0.69949,0.2955213,0.00001402788,0.000006721762,0.00008162576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981619,0.0001981311,0.0179748,0.00000517119,0.0001242793,0.0000275794,0.00001007567,0.00003268472,0.000008262479],"genre_scores_gemma":[0.9920234,0.0002116001,0.007715719,0.000002530548,0.00002229075,8.334209e-7,0.000004326881,0.00001541342,0.000003883747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1868758,"threshold_uncertainty_score":0.4127082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009779467821611036,"score_gpt":0.243882595070865,"score_spread":0.234103127249254,"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."}}