{"id":"W4319601952","doi":"10.1016/j.jmst.2022.11.047","title":"Adiabatic shear instability in a titanium alloy: Extreme deformation-induced phase transformation, nanotwinning, and grain refinement","year":2023,"lang":"en","type":"article","venue":"Journal of Material Science and Technology","topic":"Microstructure and mechanical properties","field":"Materials Science","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Materials science; Adiabatic shear band; Diffusionless transformation; Deformation (meteorology); Martensite; Titanium alloy; Instability; Deformation mechanism; Split-Hopkinson pressure bar; Shear (geology); High-resolution transmission electron microscopy; Composite material; Dislocation; Strain rate; Metallurgy; Transmission electron microscopy; Alloy; Microstructure; Mechanics; Nanotechnology; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002011865,0.00008854797,0.0002071651,0.000467607,0.0001551321,0.00009665897,0.0002198531,0.00008361338,0.00009035514],"category_scores_gemma":[0.0002761012,0.00006147386,0.000012954,0.0006839227,0.0003250995,0.0006312989,0.00008411475,0.00009837275,0.000007240005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006322691,"about_ca_system_score_gemma":0.0001466569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003005279,"about_ca_topic_score_gemma":0.00002737018,"domain_scores_codex":[0.9988157,0.00003194333,0.000481285,0.0001464726,0.0002652985,0.0002593427],"domain_scores_gemma":[0.9994898,0.00001106986,0.0001584943,0.0001038259,0.0001694668,0.00006736737],"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":[0.00004950599,0.00002008136,0.00004534085,0.00002897574,0.000001145592,0.000005537398,0.0006281877,6.173099e-7,0.992266,0.001298588,0.00004688442,0.005609147],"study_design_scores_gemma":[0.0009938654,0.0005632668,0.0006519106,0.0000606904,0.000007570091,0.0001179029,0.0009954451,0.0001847075,0.988686,0.00582278,0.001810929,0.0001049528],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970516,0.00003392635,0.00003284852,0.002192389,0.0004644733,0.0001370118,0.00000581529,0.00003662094,0.00004531934],"genre_scores_gemma":[0.9993984,0.00005350441,0.0004368378,0.0000714184,0.00002532256,0.000004812263,6.630951e-7,0.000003705367,0.000005347576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005504194,"threshold_uncertainty_score":0.2506831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251258274656657,"score_gpt":0.2680446061085289,"score_spread":0.2429187786428632,"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."}}