{"id":"W2606427320","doi":"10.1016/j.actamat.2017.04.024","title":"Ab initio modelling of solute segregation energies to a general grain boundary","year":2017,"lang":"en","type":"article","venue":"Acta Materialia","topic":"Microstructure and mechanical properties","field":"Materials Science","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"H2020 European Research Council; Natural Sciences and Engineering Research Council of Canada; European Commission; Western Canada Research Grid; Compute Canada","keywords":"Grain boundary; Materials science; Boundary (topology); Ab initio; Tilt (camera); Work (physics); Quantum; Range (aeronautics); Ab initio quantum chemistry methods; Thermodynamics; Statistical physics; Condensed matter physics; Physics; Microstructure; Quantum mechanics; Geometry; Metallurgy; Molecule; Mathematical analysis","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":[0.0002876875,0.0002818266,0.0004919802,0.000517134,0.0007731742,0.0006027481,0.0008837479,0.001025361,0.001339288],"category_scores_gemma":[0.0005833068,0.0002865556,0.0004579539,0.0004816114,0.0006995511,0.0004488336,0.0006017353,0.000458091,0.0002093323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031544,"about_ca_system_score_gemma":0.0009793176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009092076,"about_ca_topic_score_gemma":0.005637764,"domain_scores_codex":[0.9999044,0.00001892171,0.000004124304,0.00001279785,0.00003559696,0.00002402438],"domain_scores_gemma":[0.9998688,0.00004511512,0.00001545923,0.00002274382,0.00003043796,0.00001744781],"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":[0.00003617971,0.00004390187,0.0009091632,0.00005038676,0.00001409631,0.000118769,0.00005018707,0.9616929,0.009263285,0.02509978,0.0002037972,0.002517532],"study_design_scores_gemma":[0.000007431854,0.000008528826,0.0001814443,0.000002821823,0.000002066323,0.000005148548,0.000007716056,0.9969379,0.0006796106,0.002028366,0.0001359383,0.000003007421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9148785,0.0002366473,0.06839326,0.0003589546,0.0000283942,0.00005922535,0.0002335667,0.0002189814,0.01559251],"genre_scores_gemma":[0.9830193,0.0001339779,0.01516431,0.00005535344,0.00001122153,0.00009602786,0.0001037489,0.00005317149,0.001362912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009092076,"threshold_uncertainty_score":0.01807827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05230375204010684,"score_gpt":0.2690810124809891,"score_spread":0.2167772604408823,"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."}}