{"id":"W4246733687","doi":"10.32920/ryerson.14652267","title":"IC testing using thermal image based on intelligent classification methods","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Support vector machine; Feature extraction; Computer science; Adaptive neuro fuzzy inference system; Histogram; Perceptron; Fuzzy logic; Segmentation; Artificial neural network; Image (mathematics); Fuzzy control system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003694283,0.0005360239,0.0005413136,0.001422698,0.0001831063,0.0008105626,0.0006508949,0.0006987386,0.001052033],"category_scores_gemma":[0.001261274,0.0001906362,0.0004590595,0.0007255504,0.0003819764,0.0007660263,0.0002586016,0.0002898677,0.0004748022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003873153,"about_ca_system_score_gemma":0.0002612486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001294655,"about_ca_topic_score_gemma":0.001012422,"domain_scores_codex":[0.9995853,0.00005974439,0.0000313569,0.0001074548,0.000172256,0.0000437996],"domain_scores_gemma":[0.9995108,0.0001417492,0.00009455698,0.00005602182,0.0001811517,0.00001576513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002131661,0.0001336648,0.003810633,0.0001837533,0.00006781829,0.0001462756,0.0001242335,0.1001693,0.0746334,0.004711855,0.001387442,0.8144183],"study_design_scores_gemma":[0.000008095773,0.00005820014,0.002327216,0.00001701316,0.00002201554,0.000109597,0.0000236373,0.9746636,0.02042942,0.001419504,0.000906714,0.00001506605],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04106793,0.0002665851,0.9551522,0.00007434334,0.00003942295,0.00004424143,0.00003245863,0.001157045,0.002165881],"genre_scores_gemma":[0.6189532,0.0003264711,0.377762,0.00009000983,0.00005951397,0.0001042601,0.000131259,0.00006618762,0.002507102],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001422698,"threshold_uncertainty_score":0.003519356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1928518437463194,"score_gpt":0.3724424168196926,"score_spread":0.1795905730733732,"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."}}