{"id":"W4242725658","doi":"10.32920/ryerson.14649096","title":"Statistics Based Neural Networks Method for Industrial Image Inspection","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Artificial neural network; Computer science; Artificial intelligence; Image (mathematics); Pixel; Pattern recognition (psychology); Set (abstract data type); Computer vision","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":[0.0006433286,0.0006588449,0.000663802,0.001359495,0.0002465356,0.000572608,0.0008603545,0.000692352,0.001578137],"category_scores_gemma":[0.001692228,0.0003339193,0.0006492621,0.001262342,0.0004691466,0.0009387275,0.0004908953,0.0008955534,0.0004977902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008219465,"about_ca_system_score_gemma":0.0009549746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005870145,"about_ca_topic_score_gemma":0.004044156,"domain_scores_codex":[0.9994324,0.0001055854,0.00003747664,0.0001384935,0.0002491253,0.00003686649],"domain_scores_gemma":[0.9994354,0.000221986,0.00007478274,0.00004132511,0.0002080542,0.00001848959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001335381,0.00007504033,0.001538704,0.0001391262,0.00008776259,0.00009700408,0.00007166315,0.5671013,0.01254069,0.0151982,0.002732922,0.400284],"study_design_scores_gemma":[0.000002473486,0.00001566064,0.0002587051,0.000003484885,0.000006830217,0.00001667225,0.00000330835,0.9955918,0.001477422,0.002060601,0.0005571767,0.000005760078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005588256,0.0003461163,0.9922332,0.00008278099,0.00003717206,0.00002230906,0.00003232859,0.000652038,0.001005945],"genre_scores_gemma":[0.532607,0.001506177,0.4529952,0.0002382314,0.0002459236,0.000304492,0.0003985845,0.0002787994,0.01142573],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005870145,"threshold_uncertainty_score":0.01167196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04581650831560533,"score_gpt":0.2957206449281434,"score_spread":0.2499041366125381,"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."}}