{"id":"W4395962078","doi":"10.18280/jesa.570208","title":"Enhancing Overall Equipment Effectiveness in Indonesian Automotive SMEs: A TPM Approach","year":2024,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indonesian; Total productive maintenance; Automotive industry; Overall equipment effectiveness; Manufacturing engineering; Business; Automotive engineering; Indonesian government; Engineering; Production (economics); Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003270665,0.0004360396,0.0005787924,0.001158459,0.0004030284,0.002267245,0.0004920699,0.0001147828,0.0002118017],"category_scores_gemma":[0.000219855,0.000372889,0.0002585216,0.001060474,0.000109589,0.002408667,0.0003603124,0.0006386766,0.000465147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005851149,"about_ca_system_score_gemma":0.00009591514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004062909,"about_ca_topic_score_gemma":0.00007251283,"domain_scores_codex":[0.9967617,0.0002971184,0.0009224858,0.0005501129,0.0007437055,0.0007248237],"domain_scores_gemma":[0.9990176,0.0002129919,0.000275616,0.0002815883,0.0001586931,0.0000534895],"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":[0.0005417759,0.002468163,0.03468062,0.04995474,0.002160094,0.009211652,0.007242642,0.02007761,0.00402034,0.3684115,0.01214523,0.4890857],"study_design_scores_gemma":[0.001882153,0.0001118921,0.8120031,0.005930889,0.0002372738,0.0003775973,0.001569077,0.1194804,0.0001400487,0.03814105,0.01899421,0.001132352],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.880769,0.002127435,0.06575771,0.0008627364,0.001977545,0.001287421,0.000007264986,0.000991034,0.04621983],"genre_scores_gemma":[0.9965307,0.00006419346,0.001194384,0.0004908362,0.001039352,0.0000712001,0.00001501242,0.00009046222,0.0005039251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7773224,"threshold_uncertainty_score":0.9998723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0216656694862564,"score_gpt":0.2588884264343552,"score_spread":0.2372227569480988,"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."}}