{"id":"W4401360951","doi":"10.1109/iccsc62074.2024.10617179","title":"Improved Real Time Printed Circuit Board Fault Detection","year":2024,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Printed circuit board; Computer science; Fault detection and isolation; Fault (geology); Artificial intelligence; Geology; Operating 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001592662,0.0001186231,0.000122612,0.0001378081,0.0000419694,0.0001209127,0.00004390664,0.0001746951,0.0003125281],"category_scores_gemma":[0.00001455874,0.0001022072,0.00008455434,0.0002773414,0.000006483871,0.0001293584,0.00001070099,0.0001915225,0.001066783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001264361,"about_ca_system_score_gemma":0.00001118591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002366896,"about_ca_topic_score_gemma":0.00002919944,"domain_scores_codex":[0.9993182,0.00001752976,0.000212432,0.0001721541,0.0001094458,0.0001702623],"domain_scores_gemma":[0.9997312,0.00003146243,0.000009828374,0.0001433056,0.0000285685,0.00005561179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007416564,0.000003173119,0.000001930262,0.00004795767,0.00004483852,0.000005832688,0.00006893825,0.0003917011,0.8629071,0.00009331836,0.001533688,0.1348942],"study_design_scores_gemma":[0.0002745929,0.000121296,0.0001189339,0.00006488933,0.000022056,0.00003710919,0.00005124137,0.6280787,0.3047597,0.0000819463,0.06610387,0.0002857176],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6598914,0.0001406672,0.1346109,0.00002342312,0.007307532,0.0006848599,0.000009687868,0.008829569,0.188502],"genre_scores_gemma":[0.9934349,0.000009931856,0.00003041543,0.000004569396,0.0004913171,0.00002304624,0.000002364361,0.00003695261,0.005966491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.627687,"threshold_uncertainty_score":0.999711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01281559348277548,"score_gpt":0.2217007828970088,"score_spread":0.2088851894142333,"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."}}