{"id":"W2314978389","doi":"10.1103/physreve.89.042304","title":"Predicting plasticity with soft vibrational modes: From dislocations to glasses","year":2014,"lang":"en","type":"article","venue":"Physical Review E","topic":"High-pressure geophysics and materials","field":"Earth and Planetary Sciences","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Phonon; Polarization (electrochemistry); Dislocation; Materials science; Plasticity; Molecular physics; Condensed matter physics; Soft modes; Molecular vibration; Chemical physics; Physics; Optics; Chemistry; Optoelectronics; Raman spectroscopy; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001412565,0.0002734024,0.0002206758,0.0005618219,0.0001274295,0.0003801814,0.0003293125,0.0003792891,0.000483193],"category_scores_gemma":[0.000945306,0.0001689478,0.0001941735,0.0003825795,0.0005191601,0.0005435036,0.0003404925,0.0002749565,0.00008395631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001932944,"about_ca_system_score_gemma":0.000154364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002067675,"about_ca_topic_score_gemma":0.002280028,"domain_scores_codex":[0.9999568,0.000007855087,0.000002006635,0.00001426275,0.00001093254,0.000008067736],"domain_scores_gemma":[0.9997523,0.0001003464,0.00006594542,0.00003091351,0.00002672643,0.000023835],"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":[0.0002918623,0.0001498096,0.1165872,0.0005343122,0.000168877,0.0006043561,0.000455565,0.4966912,0.2458632,0.02346104,0.001596894,0.1135957],"study_design_scores_gemma":[0.00001426873,0.00006108442,0.03653194,0.00001704559,0.0000313237,0.00007949926,0.0001293103,0.9294096,0.01405741,0.0190284,0.0006121416,0.0000279838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486496,0.0007237252,0.04912237,0.0001827728,0.00001091945,0.00001075999,0.0001035834,0.0001255784,0.001070747],"genre_scores_gemma":[0.9955664,0.0002364705,0.003947953,0.00000804208,0.00001001717,0.000004715932,0.00005466121,0.00001039048,0.0001612294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002067675,"threshold_uncertainty_score":0.00411129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01258490993226904,"score_gpt":0.2413953784834065,"score_spread":0.2288104685511375,"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."}}