{"id":"W2762072022","doi":"10.1016/j.actamat.2017.10.027","title":"Using architectured materials to control localized shear fracture","year":2017,"lang":"en","type":"article","venue":"Acta Materialia","topic":"Microstructure and Mechanical Properties of Steels","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Materials science; Martensite; Microstructure; Electron backscatter diffraction; Composite material; Shear (geology); Transmission electron microscopy; Shear band; Optical microscope; Softening; Metallurgy; Scanning electron microscope; Nanotechnology","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":[0.0001386814,0.0003577663,0.0002000797,0.000323336,0.0002014856,0.0004209506,0.0004155833,0.0002939305,0.001157379],"category_scores_gemma":[0.0002282906,0.0002409103,0.00009965558,0.0001915524,0.0003051697,0.0003084098,0.0004090327,0.0003490456,0.0002689209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002711737,"about_ca_system_score_gemma":0.000200989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002048539,"about_ca_topic_score_gemma":0.001129321,"domain_scores_codex":[0.9999232,0.000006849434,0.000004411677,0.00001695561,0.00003372461,0.0000148398],"domain_scores_gemma":[0.9998674,0.00002319925,0.00003382525,0.00002647955,0.00003071913,0.00001821981],"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":[0.00007732127,0.00004110632,0.0002571071,0.00005851402,0.00000718578,0.00003454669,0.0000255741,0.008786702,0.9793632,0.001829198,0.0002017888,0.009317712],"study_design_scores_gemma":[0.00006580564,0.0004267515,0.001697234,0.00001089887,0.00002636498,0.00006678394,0.00004148988,0.1107824,0.878433,0.001565681,0.006853915,0.0000296074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9085013,0.0007840779,0.08231223,0.0001496629,0.0002399881,0.0000414458,0.0001092395,0.0008515034,0.007010464],"genre_scores_gemma":[0.9852248,0.0001442082,0.01313818,0.00003610116,0.00001430434,0.00002072917,0.00003534099,0.00005015228,0.00133611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001157379,"threshold_uncertainty_score":0.003871799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02129414684004375,"score_gpt":0.2540561362880998,"score_spread":0.232761989448056,"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."}}