{"id":"W2514517669","doi":"10.1016/j.ultramic.2016.08.005","title":"Cross-sectional measurement of grain boundary segregation using WDS","year":2016,"lang":"en","type":"article","venue":"Ultramicroscopy","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Université de Sherbrooke","keywords":"Grain boundary; Materials science; Chemistry; Crystallography; Microstructure","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001171072,0.0001934552,0.00016342,0.0004145053,0.000299869,0.0002899255,0.0002592628,0.0002703456,0.001466798],"category_scores_gemma":[0.0001998453,0.0002116433,0.00006813495,0.0002678283,0.0002400372,0.0003106739,0.0002331897,0.0002396818,0.0002614901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002267383,"about_ca_system_score_gemma":0.0001631184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001322226,"about_ca_topic_score_gemma":0.002825347,"domain_scores_codex":[0.9999201,0.000005101394,0.000005255795,0.00002098698,0.00003529151,0.00001321019],"domain_scores_gemma":[0.999756,0.00005232122,0.0000464173,0.00003671693,0.00008497288,0.00002359274],"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":[0.00003645436,0.00002565307,0.0008334413,0.00001140077,0.000002373417,0.00002378879,0.00002560898,0.00007521702,0.9973233,0.0001206087,0.00004074958,0.00148135],"study_design_scores_gemma":[0.000005715238,0.00006580316,0.01502817,0.000002221986,0.00000678893,0.0001171598,0.00005513429,0.003519275,0.9804636,0.00005120759,0.0006808352,0.000004177547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867454,0.000144234,0.01097825,0.00002709115,0.000010958,0.00001355443,0.0001907587,0.0002056101,0.001684128],"genre_scores_gemma":[0.9902896,0.00007045494,0.008447384,0.00002576843,0.000002904159,0.00001257401,0.00009271527,0.00001999178,0.001038498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001466798,"threshold_uncertainty_score":0.004906952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0319418122351757,"score_gpt":0.2897888831959898,"score_spread":0.2578470709608141,"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."}}