{"id":"W4376126001","doi":"10.5430/jms.v14n1p1","title":"Exploring the Common Failures and Routine Maintenance of Jeans Overlocking Machine","year":2023,"lang":"en","type":"article","venue":"Journal of Management and Strategy","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Troubleshooting; Production line; Production (economics); Overall equipment effectiveness; Total productive maintenance; Rework; Originality; Preventive maintenance; Corrective maintenance; Computer science; Machine tool; Reliability engineering; Manufacturing engineering; Engineering; Industrial engineering; Artificial intelligence; Mechanical engineering; Embedded system","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":[0.001813346,0.0006624196,0.0004197946,0.002785638,0.00110563,0.001625583,0.001103884,0.0007455752,0.001952462],"category_scores_gemma":[0.006594818,0.0003490351,0.0005587494,0.001656924,0.001292239,0.001961609,0.0009812472,0.0006008098,0.0002275861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00184343,"about_ca_system_score_gemma":0.001787522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007364584,"about_ca_topic_score_gemma":0.009465345,"domain_scores_codex":[0.9973099,0.0007306017,0.000183345,0.0004731742,0.001060959,0.0002420734],"domain_scores_gemma":[0.9927246,0.002817936,0.001998885,0.0005556428,0.001687096,0.0002159069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006959236,0.0005081825,0.3486053,0.002557863,0.0002063784,0.00404552,0.02683004,0.03002158,0.01977798,0.01489504,0.005286583,0.5465698],"study_design_scores_gemma":[0.0000653495,0.002339106,0.7092439,0.001648988,0.0005041828,0.006334695,0.07291384,0.1187386,0.02147922,0.0222975,0.04414773,0.0002868777],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9166651,0.001690815,0.06798832,0.000951437,0.00007127388,0.0002620448,0.0002405436,0.0002605882,0.0118698],"genre_scores_gemma":[0.9785946,0.0005081083,0.01821261,0.00004980675,0.00001598902,0.00006623023,0.0001339508,0.00002720907,0.002391611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007364584,"threshold_uncertainty_score":0.01464343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05864426652531165,"score_gpt":0.2394161618455132,"score_spread":0.1807718953202015,"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."}}