{"id":"W2183194589","doi":"10.1007/s00170-015-7557-5","title":"Extension of flow stress–strain curves of aerospace alloys after necking","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; École de Technologie Supérieure; National Research Council Canada","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Necking; Materials science; Flow stress; Hardening (computing); Tensile testing; Strain hardening exponent; Structural engineering; Stress (linguistics); Mechanics; Work hardening; Composite material; Ultimate tensile strength; Strain rate; Microstructure; Engineering; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004380725,0.0004057414,0.000320426,0.0008172215,0.000428805,0.000551987,0.000477067,0.0006984913,0.00395946],"category_scores_gemma":[0.001153556,0.0002097851,0.0003739667,0.0006571305,0.0006718814,0.0005314172,0.0002438754,0.0005584272,0.0003098495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004490919,"about_ca_system_score_gemma":0.0005055963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004629634,"about_ca_topic_score_gemma":0.003814271,"domain_scores_codex":[0.9998674,0.00001517171,0.000006607417,0.00002471661,0.0000465568,0.0000394826],"domain_scores_gemma":[0.9993061,0.0002744413,0.0001150361,0.00006698071,0.000184894,0.00005255045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004025012,0.0008873466,0.03673729,0.000467433,0.00008160666,0.00210706,0.003315543,0.3769177,0.4712607,0.007758227,0.002339808,0.09410218],"study_design_scores_gemma":[0.00006229078,0.001339555,0.1223478,0.0001111569,0.00005845152,0.0004129444,0.0007685642,0.6382298,0.2297146,0.00195936,0.004871125,0.0001244209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891439,0.0001949472,0.004989543,0.00006164301,0.00002664515,0.00002547002,0.0003531208,0.0002135289,0.004991194],"genre_scores_gemma":[0.9970093,0.00005718657,0.0008800363,0.000008677126,0.00000390046,0.000009027689,0.0002000701,0.00003002067,0.00180165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004629634,"threshold_uncertainty_score":0.01324564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012855577950312,"score_gpt":0.2582288721716013,"score_spread":0.2453732942212893,"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."}}