{"id":"W4406314466","doi":"10.1088/2515-7639/ada9c3","title":"Understanding the influence of hydrogen on BCC iron grain boundaries using the kinetic activation relaxation technique (k-ART)","year":2025,"lang":"en","type":"article","venue":"Journal of Physics Materials","topic":"Powder Metallurgy Techniques and Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Kinetic energy; Grain boundary; Relaxation (psychology); Hydrogen; Activation energy; Materials science; Thermodynamics; Chemistry; Metallurgy; Physical chemistry; Physics; Microstructure; Classical mechanics; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000806334,0.0001215834,0.0002489132,0.00007680536,0.0001273435,0.0001354716,0.0001992248,0.00006137972,0.00001311553],"category_scores_gemma":[0.00006878273,0.00007455424,0.0000589526,0.0001624541,0.000104091,0.0002223521,0.00003121547,0.0001027405,7.384153e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000161002,"about_ca_system_score_gemma":0.00005502419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009557827,"about_ca_topic_score_gemma":5.204573e-7,"domain_scores_codex":[0.9990305,0.0001150478,0.0004958816,0.00005959069,0.0001835864,0.0001153545],"domain_scores_gemma":[0.9992302,0.00007273653,0.0004305649,0.0001836621,0.00006993931,0.00001291526],"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":[0.00002891003,0.00001089403,0.000002688772,0.00008393893,0.00003941044,4.523538e-7,0.0001688635,0.02460658,0.9556209,0.01909007,0.0002695236,0.00007772904],"study_design_scores_gemma":[0.0001038659,0.00004563759,0.0001437831,0.0003825652,0.00004972424,0.000005158221,0.00005236518,0.0001448336,0.9423964,0.05587415,0.0007355811,0.00006592613],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.843951,0.00001590525,0.1550062,0.0001386709,0.000374255,0.0002452343,0.000005648467,0.00003288588,0.0002302083],"genre_scores_gemma":[0.9992055,0.00004626072,0.0005487105,0.00005133743,0.0001030918,0.00001023639,0.000001810048,0.00001654104,0.00001652776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1552545,"threshold_uncertainty_score":0.3040234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02831906834659003,"score_gpt":0.2604481973445472,"score_spread":0.2321291289979571,"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."}}