{"id":"W2161020264","doi":"10.1016/j.matchar.2014.04.009","title":"Potential and limitations of microanalysis SEM techniques to characterize borides in brazed Ni-based superalloys","year":2014,"lang":"en","type":"article","venue":"Materials Characterization","topic":"Advanced Materials Characterization Techniques","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Agence Nationale de la Recherche","keywords":"Microanalysis; Superalloy; Materials science; Boron; Boride; Scanning electron microscope; Brazing; Metallurgy; Energy-dispersive X-ray spectroscopy; Micrometer; Alloy; Analytical Chemistry (journal); Optics; Composite material; Chemistry","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":[0.0003546176,0.0003134703,0.0005968458,0.0005074087,0.00008038217,0.0002388498,0.0001773454,0.0001733091,0.0000644613],"category_scores_gemma":[0.0001640349,0.0003497607,0.00003997568,0.0003944163,0.0000473249,0.0005272657,0.00005605291,0.000064489,0.000008620429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006085887,"about_ca_system_score_gemma":0.00001485936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002018868,"about_ca_topic_score_gemma":0.00001016651,"domain_scores_codex":[0.9981819,0.0001392345,0.0008746576,0.0003373804,0.0001739867,0.0002927926],"domain_scores_gemma":[0.9992061,0.00006141393,0.000190933,0.0003220802,0.0001299463,0.00008957576],"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":[0.00005457762,0.00003550169,0.0002588305,0.000174973,0.00001241158,0.000001125934,0.0001327446,0.0000879254,0.9934731,0.00009258161,0.000009561129,0.00566665],"study_design_scores_gemma":[0.0002592948,0.00006290233,0.05397404,0.0001225887,0.00002398847,0.000002441299,0.000007413427,0.0008660072,0.9425336,0.00009811131,0.001727618,0.0003220342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8971723,0.000003356074,0.1009481,0.0001571402,0.0002955951,0.0005414895,0.0002508344,0.000581012,0.00005019363],"genre_scores_gemma":[0.98629,0.0001795448,0.01109413,0.0002518061,0.0001435028,0.0002166355,0.001693762,0.00009238787,0.00003819706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08985396,"threshold_uncertainty_score":0.9998955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108321891862976,"score_gpt":0.2092636071322978,"score_spread":0.1984314179460002,"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."}}