{"id":"W2071506646","doi":"10.4028/www.scientific.net/msf.706-709.2066","title":"Dual Phase Steel Characterization for Tube Bending and Hydroforming Applications","year":2012,"lang":"en","type":"article","venue":"Materials science forum","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Ontario Centres of Excellence","keywords":"Materials science; Hydroforming; Bending; Dual-phase steel; Nanoindentation; Composite material; Ultimate tensile strength; Tube (container); Martensite; Formability; Elongation; Metallurgy; Microstructure","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005760767,0.000095006,0.0001109481,0.0001453468,0.000258015,0.0001224522,0.00009633903,0.00003611202,0.00003091453],"category_scores_gemma":[0.00002748433,0.00009258487,0.00001317139,0.000180899,0.00007491831,0.001227471,0.00004464742,0.00002090038,0.000009135601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000447528,"about_ca_system_score_gemma":0.000008825762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001005524,"about_ca_topic_score_gemma":1.62991e-7,"domain_scores_codex":[0.9991693,0.000004555603,0.000208451,0.0001230017,0.0001254029,0.0003693106],"domain_scores_gemma":[0.9996911,0.0000189543,0.00004578654,0.0001301642,0.00003031839,0.00008363342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000219044,0.00001023814,0.00009334388,0.00003643639,0.000001441164,1.937938e-8,0.00009999397,0.000006841032,0.9813822,0.01124485,0.000009776176,0.007112664],"study_design_scores_gemma":[0.0001567954,0.00002409982,0.0004414675,0.00001191502,0.000006356247,0.000005257805,0.00003500693,0.00447682,0.985867,0.0006013748,0.008246437,0.0001274273],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9255453,0.00001886207,0.07294937,0.00002383322,0.0003994915,0.0005373953,0.00008004165,0.0002969479,0.0001487693],"genre_scores_gemma":[0.994758,0.000007108066,0.004732214,0.00002098806,0.0001338278,0.0002340021,0.00005947657,0.00001826822,0.00003619369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06921263,"threshold_uncertainty_score":0.3775501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01649163541094625,"score_gpt":0.2884397800913779,"score_spread":0.2719481446804316,"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."}}