{"id":"W4379795519","doi":"10.23977/jaip.2023.060309","title":"Applications and challenges of hybrid artificial intelligence in chip age testing: a comprehensive review","year":2023,"lang":"en","type":"review","venue":"Journal of Artificial Intelligence Practice","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reliability (semiconductor); Computer science; Artificial intelligence; Adaptation (eye); Artificial neural network; Genetic algorithm; Convolutional neural network; Machine learning; Generalization; Deep learning; Stability (learning theory); Evolutionary algorithm; Reliability engineering; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002515152,0.0004130146,0.002066695,0.0007418632,0.00006996606,0.00008184454,0.0003702334,0.0002382333,0.00001266129],"category_scores_gemma":[0.003500798,0.0003650933,0.0003430714,0.001406722,0.0001027067,0.0003701953,0.00007660459,0.001369414,0.00009557355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001376588,"about_ca_system_score_gemma":0.0001938311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003975955,"about_ca_topic_score_gemma":0.00001720107,"domain_scores_codex":[0.9949678,0.000487112,0.003443318,0.0003135667,0.0004920156,0.0002962554],"domain_scores_gemma":[0.9929371,0.003895907,0.002029141,0.000348313,0.0006507022,0.000138809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001772068,0.00007002299,3.277903e-8,0.02543269,0.0001192678,0.0001329741,0.000101611,0.0004249121,0.00001330996,0.001215275,0.00003531709,0.9724368],"study_design_scores_gemma":[0.00001656765,0.0003421377,3.528852e-7,0.06988478,0.0009076899,0.001575835,0.001309667,0.001052235,0.000249363,0.003489974,0.9206668,0.0005046286],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000006977353,0.9844905,0.01305693,0.0001172547,0.000797678,0.001150271,0.000015923,0.00005217273,0.0003122988],"genre_scores_gemma":[0.0002692261,0.9977272,0.001147029,0.00001646149,0.0006924635,0.00007228415,0.000002823433,0.00006876034,0.000003733147],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9719322,"threshold_uncertainty_score":0.9998801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3448067366208292,"score_gpt":0.4146184699396857,"score_spread":0.06981173331885648,"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."}}