{"id":"W4220947068","doi":"10.1002/cjce.24405","title":"Experimental methods in chemical engineering: Scanning electron microscopy and<scp>X</scp>‐ray ultra‐microscopy—<scp>SEM</scp>and<scp>XuM</scp>","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"","keywords":"Scanning electron microscope; Magnification; Resolution (logic); Materials science; Energy-dispersive X-ray spectroscopy; Microscopy; Nanotechnology; Analytical Chemistry (journal); Optics; Chemistry; Composite material; Computer science; Physics; Chromatography; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001694344,0.0006029592,0.0008247906,0.0005447847,0.0002941578,0.0003306653,0.001019726,0.0002477696,0.00002853157],"category_scores_gemma":[0.001214396,0.000583034,0.0001923427,0.0006492031,0.0002375358,0.0003185958,0.0001688903,0.002020656,0.000003115935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001287035,"about_ca_system_score_gemma":0.0005573141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007089011,"about_ca_topic_score_gemma":0.00002667195,"domain_scores_codex":[0.9962461,0.0001436455,0.0009019561,0.0005608656,0.0004951059,0.001652337],"domain_scores_gemma":[0.9972785,0.000989807,0.0003190813,0.0003727583,0.00008211062,0.0009577154],"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":[0.000006004451,0.00003506038,0.0001336695,0.00004837917,0.00003729383,0.00006360369,0.001899832,0.001186987,0.995021,0.0003859077,0.00113753,0.00004468888],"study_design_scores_gemma":[0.0005840276,0.0002435723,0.00006361691,0.0001281085,0.00004304218,0.0007217839,0.0002849881,0.001870623,0.9872941,0.000112225,0.008519858,0.0001339923],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892415,0.007305181,0.002237455,0.0001573439,0.0004293665,0.0002990406,0.00002123025,0.000135603,0.0001733287],"genre_scores_gemma":[0.9669391,0.00003856405,0.0321586,0.0002476161,0.0003036776,0.00006583861,0.000008770895,0.0001372445,0.0001005834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02992115,"threshold_uncertainty_score":0.9996621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008153573835206875,"score_gpt":0.2749888404754659,"score_spread":0.266835266640259,"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."}}