{"id":"W4413020850","doi":"10.1111/jmi.70018","title":"Comparison of two Monte Carlo approaches for homogeneous bulk samples","year":2025,"lang":"en","type":"article","venue":"Journal of Microscopy","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Homogeneous; Standard deviation; Monte Carlo method; Computational physics; Range (aeronautics); Spectral line; Software; Binary number; Mean squared error; Materials science; Microanalysis; Analytical Chemistry (journal); Physics; Computer science; Statistical physics; Statistics; 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":[0.001661826,0.0005994647,0.0009081396,0.001107464,0.0006005667,0.001001022,0.001305658,0.000934727,0.00368703],"category_scores_gemma":[0.005571703,0.0004170801,0.0006146819,0.0009772019,0.0003790151,0.0008768581,0.0004749783,0.0006452401,0.0006080015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064934,"about_ca_system_score_gemma":0.001470369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0116583,"about_ca_topic_score_gemma":0.0122916,"domain_scores_codex":[0.9994842,0.0001435812,0.00002923986,0.0000972686,0.0001979252,0.00004786059],"domain_scores_gemma":[0.9964206,0.002423731,0.0001241421,0.0003176714,0.0006379873,0.00007592711],"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":[0.0003290588,0.0001149774,0.002376954,0.0002608198,0.0001167615,0.00007726431,0.000130057,0.9422103,0.005991565,0.01011436,0.001166514,0.03711136],"study_design_scores_gemma":[0.00001429569,0.0000373631,0.0003151587,0.00001342927,0.0000198692,0.00002559132,0.00002945532,0.994377,0.002628667,0.00174528,0.0007825154,0.00001145529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.260931,0.001786575,0.713018,0.000290432,0.000126607,0.0003796208,0.001077187,0.003999542,0.01839104],"genre_scores_gemma":[0.6912354,0.000740341,0.3015856,0.0001611188,0.00003401865,0.0004662975,0.00103915,0.001027253,0.003710904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0116583,"threshold_uncertainty_score":0.0231809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04635691577439235,"score_gpt":0.3684296386881974,"score_spread":0.3220727229138051,"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."}}