{"id":"W2893102594","doi":"10.1088/1757-899x/418/1/012089","title":"Prediction of DP600 and TRIP780 yield loci using Yoshida anisotropic yield function","year":2018,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Metal Forming Simulation Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; ArcelorMittal","keywords":"Anisotropy; Materials science; Flow stress; Yield (engineering); Plane stress; Plasticity; Structural engineering; Composite material; Strain rate; Physics; Engineering; Finite element method","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":[0.0004993889,0.0005222736,0.0002496568,0.0006286675,0.0001576762,0.0002899355,0.0003621565,0.0005921134,0.0004404068],"category_scores_gemma":[0.00100073,0.0002538321,0.000308581,0.0002940415,0.0002218809,0.0002627957,0.0001730229,0.0002459164,0.0001894121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004217308,"about_ca_system_score_gemma":0.0004652388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00468662,"about_ca_topic_score_gemma":0.004801602,"domain_scores_codex":[0.9999099,0.00001240111,0.000004584524,0.00002257615,0.00003704517,0.00001349007],"domain_scores_gemma":[0.9996654,0.0001365007,0.00006369299,0.00002687982,0.00008898195,0.00001861843],"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":[0.0000807523,0.00005156273,0.009562393,0.00003301859,0.000007608717,0.000103771,0.00004700059,0.9355836,0.03432656,0.0006973846,0.0001629767,0.0193434],"study_design_scores_gemma":[0.000001414177,0.00001245763,0.001339912,9.538973e-7,0.000001500267,0.000006625995,0.00000396004,0.9947943,0.003731898,0.00005724582,0.00004618816,0.000003387918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8879923,0.0000723039,0.1096347,0.000029153,0.000005090289,0.0000244592,0.0001177532,0.0003697886,0.001754346],"genre_scores_gemma":[0.9837841,0.00002852071,0.01572827,0.000002745355,9.927458e-7,0.00001443361,0.00007872335,0.00003278652,0.0003295928],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00468662,"threshold_uncertainty_score":0.009318709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03839299451037743,"score_gpt":0.22447092554691,"score_spread":0.1860779310365326,"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."}}