{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000475751,0.0001150868,0.0002654504,0.0001941882,0.0000450428,0.00002571172,0.00004995717,0.0000591328,0.00002645098],"category_scores_gemma":[0.00003252204,0.0001195292,0.00006135163,0.0003036932,0.00004094731,0.0002371401,0.000007943887,0.0000364993,5.568901e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003065528,"about_ca_system_score_gemma":0.00001237245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001636384,"about_ca_topic_score_gemma":0.000006224471,"domain_scores_codex":[0.9991539,0.0001028545,0.0003630744,0.0001531135,0.0001290735,0.00009795727],"domain_scores_gemma":[0.9995474,0.00001717216,0.0001287892,0.0001520455,0.0001318267,0.00002272881],"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":[0.00001859342,0.00001521156,0.00009280008,0.00002463997,0.00006646392,6.145114e-8,0.0002194805,0.002522995,0.9956792,0.0001637649,0.000003201078,0.001193567],"study_design_scores_gemma":[0.0001456138,0.00003712404,0.002223994,0.00001837032,0.0003002105,9.547668e-7,0.00005126477,0.01738968,0.9785907,0.0011018,0.00001884261,0.0001213863],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.855146,0.0007297388,0.1437619,0.000006445531,0.00003053966,0.0001471235,0.00002129696,0.00008480209,0.00007217143],"genre_scores_gemma":[0.9626737,0.000194808,0.03703628,0.00001625307,0.000007756198,0.000005653656,0.0000530691,0.000008682898,0.000003840807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1075277,"threshold_uncertainty_score":0.4874261,"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."}}