{"id":"W4224234243","doi":"10.1002/jemt.24117","title":"An advantageous imaging perspective for quantitative evaluation of 7075 aluminum alloy grain boundary precipitates using scanning electron microscope","year":2022,"lang":"en","type":"article","venue":"Microscopy Research and Technique","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; Aluminium Refining, Degassing and Filtering (Canada)","funders":"","keywords":"Scanning electron microscope; Materials science; Grain boundary; Grain size; Microscope; Environmental scanning electron microscope; Electron microscope; Optics; Scanning transmission electron microscopy; Electron; Microstructure; Metallurgy; Composite material; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003742217,0.0002770151,0.000333266,0.0005650555,0.0008870012,0.0001553592,0.000389174,0.00007329598,0.00004089932],"category_scores_gemma":[0.0001643165,0.0003023009,0.00006495765,0.0004930262,0.0005570349,0.0004038356,0.0002119305,0.0006797168,5.535138e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138797,"about_ca_system_score_gemma":0.0004160276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004667795,"about_ca_topic_score_gemma":0.00005984622,"domain_scores_codex":[0.9972175,0.0004764182,0.0003629675,0.0005419815,0.0006201594,0.0007809669],"domain_scores_gemma":[0.9983208,0.0001533166,0.00008437414,0.0003381702,0.0009991743,0.000104212],"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":[0.0002915955,0.00005893163,0.0004204962,0.0001354657,0.00006002243,0.000003436751,0.004044774,0.001359622,0.9923646,0.0002452671,0.0003236578,0.0006921675],"study_design_scores_gemma":[0.0005703859,0.001077242,0.0000965477,0.00007855793,0.0000375885,0.00006575897,0.009171301,0.03847587,0.9435697,0.00579904,0.0007376889,0.0003203385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9752609,0.0107056,0.010423,0.00004762908,0.00012276,0.002868503,0.0002303463,0.0001946454,0.0001466386],"genre_scores_gemma":[0.9492942,0.00007537808,0.04935315,0.00001253816,0.00003528486,0.001009368,0.0000713536,0.0001157136,0.00003297165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04879488,"threshold_uncertainty_score":0.9999429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04346283676707337,"score_gpt":0.3982152678656576,"score_spread":0.3547524310985842,"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."}}