{"id":"W4312790200","doi":"10.1109/jiot.2022.3228869","title":"Real-Time Quality Inspection of Motor Rotor Using Cost-Effective Intelligent Edge System","year":2022,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Computer science; Convolutional neural network; Rotor (electric); Edge computing; Enhanced Data Rates for GSM Evolution; Microcontroller; Deep learning; Real-time computing; Embedded system; Artificial intelligence; Engineering; Electrical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001825911,0.0001681083,0.0004602223,0.0003531204,0.0001262603,0.00004377403,0.0002133169,0.0001047806,0.0001057036],"category_scores_gemma":[0.00006058898,0.0001647154,0.0002691342,0.0002295914,0.0000285417,0.0002462943,0.00005562354,0.0006315081,0.000008937736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293394,"about_ca_system_score_gemma":0.00003737489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001033589,"about_ca_topic_score_gemma":0.000001498886,"domain_scores_codex":[0.9978251,0.0003625542,0.0009727466,0.0001477926,0.000498956,0.0001928569],"domain_scores_gemma":[0.9988062,0.0001127705,0.0006274093,0.0001639252,0.0002039219,0.00008581785],"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":[0.0005206095,0.00007652734,0.0002194777,0.0003084233,0.0003168704,0.00001888611,0.003804283,0.04144192,0.9447789,0.00009671321,0.001165169,0.00725219],"study_design_scores_gemma":[0.001177782,0.001163663,0.0003636078,0.0008010109,0.00009185761,0.001221737,0.00315365,0.2986162,0.6908709,0.00003795167,0.002109062,0.0003925418],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963315,0.00006548957,0.02882412,0.000002406617,0.005677531,0.0008330872,0.00001776547,0.0001531429,0.001111447],"genre_scores_gemma":[0.9991524,0.000007128051,0.0002198313,0.000003312268,0.0004143111,0.00004915845,0.000001014516,0.00003544448,0.0001174644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2571743,"threshold_uncertainty_score":0.6716897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03463509600067306,"score_gpt":0.2879129144679047,"score_spread":0.2532778184672316,"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."}}