{"id":"W1999187242","doi":"10.1017/s1431927609097141","title":"Quantitative Evaluation of Metallographic Preparation Quality using EBSD","year":2009,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Advanced Materials Characterization Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; McGill University","funders":"","keywords":"Microanalysis; Electron backscatter diffraction; Materials science; Metallurgy; Electron probe microanalysis; Chemistry; Microstructure; Electron microprobe","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":[0.001799588,0.0005946276,0.0004371239,0.001635582,0.0004408546,0.0008229409,0.0006601196,0.0006017613,0.00980058],"category_scores_gemma":[0.00351593,0.0005198601,0.0002527102,0.001361126,0.0006036938,0.0008937624,0.0005128065,0.0006487404,0.00105966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004002767,"about_ca_system_score_gemma":0.0002180482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001257717,"about_ca_topic_score_gemma":0.002407652,"domain_scores_codex":[0.9989208,0.00009550693,0.0001648805,0.0001888804,0.0005433671,0.00008654613],"domain_scores_gemma":[0.9954561,0.001290318,0.0003241917,0.0007147692,0.002163436,0.0000511475],"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":[0.0001434189,0.00004490012,0.001077669,0.0001862631,0.00003043587,0.00006817704,0.00009288574,0.000435127,0.9816316,0.0002165237,0.0003310448,0.01574182],"study_design_scores_gemma":[0.00001696681,0.00007788333,0.008971269,0.00001507693,0.00004470054,0.0001637651,0.00006083971,0.003913084,0.9841734,0.000119902,0.002429215,0.00001382494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6911009,0.005591775,0.2785545,0.0005892502,0.000477728,0.0005682891,0.003590987,0.004394278,0.01513228],"genre_scores_gemma":[0.7975549,0.00175868,0.1848745,0.0001738168,0.00005633343,0.000330775,0.002525289,0.001206792,0.01151886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00980058,"threshold_uncertainty_score":0.03278619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04491571757165651,"score_gpt":0.3782537750776422,"score_spread":0.3333380575059857,"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."}}