{"id":"W4391100695","doi":"10.2139/ssrn.4700194","title":"Deuterium Trapping and Desorption by Vacancy Clusters in Irradiated Mo from Object Kinetic Monte Carlo Simulations","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Nuclear Materials and Properties","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Kinetic Monte Carlo; Deuterium; Monte Carlo method; Trapping; Kinetic energy; Vacancy defect; Physics; Desorption; Nuclear physics; Irradiation; Statistical physics; Chemistry; Condensed matter physics; Physical chemistry; Mathematics","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":[0.0006516905,0.0007258204,0.001243804,0.0008661881,0.0009677403,0.001520328,0.001608203,0.001482124,0.003527739],"category_scores_gemma":[0.001421989,0.0007211851,0.0008487044,0.001036092,0.001230596,0.0008751212,0.0008049944,0.0007901841,0.0002854344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002530626,"about_ca_system_score_gemma":0.001033201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0153457,"about_ca_topic_score_gemma":0.009242727,"domain_scores_codex":[0.9998034,0.00005171209,0.000008032215,0.00002238714,0.00005514702,0.00005935485],"domain_scores_gemma":[0.9993801,0.0003557501,0.00007435889,0.00005283814,0.00006939688,0.00006745242],"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":[0.000148848,0.00005725518,0.001321193,0.00008207389,0.00004444599,0.0001392353,0.0001109151,0.9694382,0.002228279,0.02512519,0.0003398129,0.0009645486],"study_design_scores_gemma":[0.00004239959,0.00001421268,0.0005923953,0.00001336762,0.00001239112,0.00001569863,0.00002446593,0.9937426,0.001242055,0.00404196,0.0002445172,0.00001396068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9387649,0.0004394821,0.03323587,0.000417348,0.00006738867,0.00009512656,0.0007957599,0.0002901264,0.025894],"genre_scores_gemma":[0.9913487,0.0001610576,0.004406926,0.0000942818,0.00002195847,0.0001010293,0.0004478804,0.0002131564,0.003205088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0153457,"threshold_uncertainty_score":0.03051275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0106338448502367,"score_gpt":0.2283579509103237,"score_spread":0.217724106060087,"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."}}