{"id":"W4327512437","doi":"10.21611/qirt.2022.3014","title":"Defect Detection Enhancement, A Survey","year":2022,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Segmentation; Conditional random field; Artificial intelligence; Image segmentation; Prior probability; Surface (topology); Pattern recognition (psychology); Computer vision; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005212761,0.00006657209,0.00007923874,0.00008472439,0.0001697359,0.00001914796,0.00004507635,0.00002326418,0.001106472],"category_scores_gemma":[0.00001635716,0.00006774133,0.00005488281,0.0003101461,0.000002795782,0.00004475708,0.00002464545,0.0001492179,0.00009660501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001191468,"about_ca_system_score_gemma":0.000005326085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003169845,"about_ca_topic_score_gemma":0.0001472931,"domain_scores_codex":[0.9993843,0.0001015912,0.0001355194,0.00009984217,0.0001548219,0.0001238635],"domain_scores_gemma":[0.9997925,0.00003740409,0.00001551877,0.0001129658,0.00001468785,0.00002693937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002455085,0.0001443785,0.003450244,0.00004508998,0.0002721809,0.00001349938,0.0003580965,0.06931528,0.5583562,0.0001308123,0.1161438,0.251525],"study_design_scores_gemma":[0.001300123,0.0008849726,0.005950168,0.000005698239,0.00001673991,0.00006682416,0.0002832915,0.05777574,0.2438616,0.00005231963,0.6891654,0.0006371249],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9165091,0.00007351127,0.06266408,0.000004468463,0.002816634,0.000218185,0.00000994306,0.000500258,0.01720382],"genre_scores_gemma":[0.9990885,0.000002632244,0.00001152319,0.00003645344,0.00004851562,0.00007917289,0.000006050562,0.00001513804,0.0007120223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5730217,"threshold_uncertainty_score":0.9998066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02305855819739432,"score_gpt":0.2184000507736798,"score_spread":0.1953414925762854,"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."}}