{"id":"W3163178460","doi":"10.18280/ts.380225","title":"Design of Automated Visual Inspection System for Beverage Industry Production Line","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production line; Conveyor belt; Visual inspection; Computer science; Automated X-ray inspection; Image processing; Computer vision; Bottle; Line (geometry); Production (economics); Perspective (graphical); Grayscale; Engineering drawing; Artificial intelligence; Beverage industry; Image (mathematics); Engineering; Mechanical engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003016088,0.0004552056,0.0004559061,0.0004160102,0.0004092923,0.0007040298,0.001269633,0.0006730562,0.003276253],"category_scores_gemma":[0.0005419352,0.000370503,0.0002959735,0.0001489401,0.0002216386,0.0004502321,0.0003029795,0.0002882193,0.0009446123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004388334,"about_ca_system_score_gemma":0.0007687214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001941578,"about_ca_topic_score_gemma":0.001135472,"domain_scores_codex":[0.9995224,0.00005476523,0.00002176296,0.0001750406,0.000173001,0.00005293358],"domain_scores_gemma":[0.9996227,0.00006167547,0.00005723054,0.00003542447,0.0001916781,0.0000312664],"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":[0.0008690878,0.0003465519,0.005510795,0.0005937129,0.0001142727,0.001048605,0.0006371973,0.06122151,0.5776234,0.003493197,0.006841882,0.3416998],"study_design_scores_gemma":[0.0003336293,0.002081787,0.01076603,0.00008017257,0.0001578584,0.001497397,0.0001669559,0.7634597,0.191344,0.0009073855,0.02910447,0.0001004796],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07424381,0.0002462703,0.9107694,0.0001653103,0.00009994299,0.0004611211,0.00009111584,0.008869177,0.00505383],"genre_scores_gemma":[0.7819157,0.0001177072,0.2108542,0.0001347447,0.00004599652,0.0003448983,0.0001465753,0.0001185876,0.006321625],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003276253,"threshold_uncertainty_score":0.01096016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0290596956529038,"score_gpt":0.2568072810681449,"score_spread":0.2277475854152411,"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."}}