{"id":"W2128962390","doi":"10.1007/s00170-015-7213-0","title":"Further development of adaptable automated visual inspection—part I: concept and scheme","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Adaptability; Scheme (mathematics); Block (permutation group theory); Focus (optics); Key (lock); Computer science; Quality (philosophy); Feature (linguistics); Perspective (graphical); Engineering; Artificial intelligence; Control engineering; Engineering drawing; Industrial engineering; Systems engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006125949,0.0004912731,0.0004774636,0.0005329949,0.0002686006,0.0007088704,0.001810383,0.0008621702,0.004418313],"category_scores_gemma":[0.0008259022,0.0002659243,0.000481158,0.000327177,0.0006073907,0.001082617,0.001267955,0.0006298309,0.001192945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004425596,"about_ca_system_score_gemma":0.0005053665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001089286,"about_ca_topic_score_gemma":0.0006558882,"domain_scores_codex":[0.9994718,0.00007364021,0.00002204196,0.0001577961,0.0002326054,0.00004208821],"domain_scores_gemma":[0.9993427,0.0000893566,0.00005620632,0.0002501853,0.0002165683,0.0000449015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000270059,0.0002134672,0.001777247,0.0002586328,0.00005608548,0.0003064045,0.0001758068,0.03226849,0.4193439,0.04278828,0.004229091,0.4983126],"study_design_scores_gemma":[0.00008987886,0.001173647,0.005975193,0.00008838194,0.0000641151,0.001268178,0.00007070198,0.7223852,0.1917805,0.01794624,0.05902858,0.0001294059],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01497869,0.0002307969,0.9776062,0.0001502512,0.0001016793,0.0002123913,0.00005541962,0.001965373,0.004699081],"genre_scores_gemma":[0.3306012,0.0003298619,0.6555477,0.0002000342,0.00008050848,0.0002911969,0.0002177819,0.0001375317,0.01259422],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004418313,"threshold_uncertainty_score":0.01478076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01771230953196497,"score_gpt":0.2624336050503203,"score_spread":0.2447212955183553,"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."}}