{"id":"W2113680258","doi":"10.1080/10589750802009355","title":"Effect of texture on acoustic emission produced by slip and twinning in AZ31B magnesium alloy—part II: clustering and neural network analysis","year":2008,"lang":"en","type":"article","venue":"Nondestructive Testing And Evaluation","topic":"Magnesium Alloys: Properties and Applications","field":"Materials Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Dalhousie University","funders":"National Research Council Canada","keywords":"Crystal twinning; Acoustic emission; Slip (aerodynamics); Magnesium alloy; Materials science; Cluster analysis; Artificial neural network; Deformation (meteorology); Magnesium; Alloy; Self-organizing map; Pattern recognition (psychology); Metallurgy; Artificial intelligence; Composite material; Computer science; Engineering; Microstructure","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002227852,0.000165153,0.000267391,0.0002853394,0.0001566765,0.0001914087,0.0001955318,0.0002463021,0.0004064355],"category_scores_gemma":[0.0008378185,0.0001359019,0.0001355398,0.0001936769,0.0002618421,0.0001804606,0.0001422474,0.0001163665,0.00005323673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002307349,"about_ca_system_score_gemma":0.00008622294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001933654,"about_ca_topic_score_gemma":0.002897306,"domain_scores_codex":[0.9998773,0.00001798778,0.000008056546,0.00002889219,0.0000522752,0.00001534745],"domain_scores_gemma":[0.9997149,0.0001225612,0.00005573725,0.00001741992,0.00006967628,0.00001962763],"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":[0.0006273423,0.00002977948,0.004645476,0.00006923778,0.0000131466,0.0001092623,0.00009890264,0.007847543,0.9700007,0.00005654915,0.00003380032,0.01646821],"study_design_scores_gemma":[0.00001762005,0.0004625405,0.08426548,0.000006506644,0.00003615483,0.000207331,0.0001684403,0.1578079,0.7565616,0.0001163884,0.0003200021,0.00003005527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980977,0.00005489393,0.001700977,0.00001019743,0.000001947742,0.000002504923,0.00001135984,0.00001122454,0.0001092069],"genre_scores_gemma":[0.9986481,0.00002937333,0.001140747,0.00000203734,8.263195e-7,0.000002394419,0.00002641532,0.000004030716,0.0001461212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001933654,"threshold_uncertainty_score":0.003844738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839443348646537,"score_gpt":0.2802245396197079,"score_spread":0.2518301061332426,"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."}}