{"id":"W7070159307","doi":"","title":"Prediction of the formation of adiabatic shear bands in high strength low alloy 4340 steel through analysis of grains and grain deformation","year":2014,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"High-Velocity Impact and Material Behavior","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adiabatic shear band; Grain size; Microstructure; Deformation (meteorology); Shear (geology); Plasticity; Strain rate; Shear band; Alloy","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":[0.0001456494,0.0004066518,0.000237788,0.000512741,0.0001638256,0.0003285761,0.0002892166,0.000599605,0.0004253991],"category_scores_gemma":[0.0003605024,0.0003436355,0.0003890212,0.0002506858,0.0002985004,0.0001619036,0.0001222632,0.0001858696,0.0001100443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006000223,"about_ca_system_score_gemma":0.0006065796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01630322,"about_ca_topic_score_gemma":0.01350927,"domain_scores_codex":[0.9999514,0.000006056592,0.0000029436,0.0000108705,0.00001883433,0.000009887892],"domain_scores_gemma":[0.9998503,0.00007126129,0.00003201191,0.000009600175,0.0000215731,0.00001525732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0000893519,0.00005690326,0.01246685,0.00004719619,0.00001272747,0.000127222,0.00003726749,0.9543173,0.02770737,0.0003105262,0.00007808522,0.004749236],"study_design_scores_gemma":[0.000005047245,0.00004762837,0.007192548,0.000001501486,0.000002979241,0.000009548222,0.000009606604,0.9893463,0.003257767,0.0000723866,0.00005009303,0.000004567096],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849153,0.00004727703,0.01397063,0.00001493206,0.000003269184,0.00002015148,0.0001049772,0.0001375271,0.0007859046],"genre_scores_gemma":[0.9967134,0.00002679549,0.002933083,0.000001633273,5.37119e-7,0.000007771769,0.00007504783,0.00001090605,0.00023081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01630322,"threshold_uncertainty_score":0.03241664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318769518745812,"score_gpt":0.2094325879702441,"score_spread":0.196244892782786,"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."}}