{"id":"W4224104393","doi":"10.1103/physrevmaterials.6.043601","title":"Atomic energy in grain boundaries studied by machine learning","year":2022,"lang":"en","type":"article","venue":"Physical Review Materials","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Amorphous solid; Nanocrystalline material; Materials science; Lattice (music); Voronoi diagram; Atomic radius; Grain boundary; Statistical physics; Nanotechnology; Crystallography; Physics; Mathematics; Quantum mechanics; Chemistry","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":[0.000398567,0.0003337669,0.0005827275,0.001539909,0.0003315412,0.0006124668,0.0007724852,0.0006881144,0.0007077458],"category_scores_gemma":[0.001419557,0.0002130498,0.0004791296,0.000968041,0.0009816913,0.001454247,0.0004759786,0.0008187906,0.0001404582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005766145,"about_ca_system_score_gemma":0.0003113478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003099496,"about_ca_topic_score_gemma":0.001724088,"domain_scores_codex":[0.9998504,0.00003169671,0.000006800018,0.00004026805,0.00004697192,0.00002388262],"domain_scores_gemma":[0.9995201,0.0002434563,0.00009949862,0.00005781286,0.00005597288,0.00002312359],"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":[0.00006776239,0.00006018756,0.01561925,0.0001968622,0.00008749241,0.0001253211,0.00007367459,0.8883396,0.005245907,0.03868854,0.001309312,0.05018606],"study_design_scores_gemma":[0.000001633914,0.000006016457,0.000996743,0.000005191592,0.000002722176,0.000007696171,0.000009316153,0.9850152,0.0005085716,0.01316444,0.0002784281,0.000004073016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.661874,0.003989239,0.3272628,0.0007258971,0.0001038634,0.00004364409,0.0003529614,0.0005556238,0.005092078],"genre_scores_gemma":[0.9774129,0.0005942133,0.02075416,0.00005762375,0.00004321751,0.00003337686,0.0003002311,0.0000445938,0.0007596958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003099496,"threshold_uncertainty_score":0.006162941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01078286825395655,"score_gpt":0.289447204484281,"score_spread":0.2786643362303245,"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."}}