{"id":"W1916751280","doi":"","title":"ANALISIS NILAI OVERALL EQUIPMENT EFFECTIVENESS (OEE) SEBAGAI DASAR UNTUK PERBAIKAN EFEKTIVITAS KERJA MESIN CUT OFF DI PLANT X PT ABC","year":2015,"lang":"id","type":"article","venue":"Jurnal Ilmiah Universitas Bakrie","topic":"Management and Optimization Techniques","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Physics; Automotive engineering; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002240464,0.0004591538,0.0005738146,0.001612849,0.0002514976,0.001148887,0.00041893,0.0004026723,0.005707723],"category_scores_gemma":[0.003632159,0.0001472498,0.0008627931,0.001291875,0.0003257276,0.0006354689,0.0005649916,0.0007512745,0.0007667332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007085452,"about_ca_system_score_gemma":0.0005794488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002448973,"about_ca_topic_score_gemma":0.004231451,"domain_scores_codex":[0.9976155,0.0004895495,0.0002489007,0.0002549444,0.001194651,0.0001966127],"domain_scores_gemma":[0.9908891,0.005256653,0.001168559,0.0002211298,0.002247933,0.0002165762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004705525,0.001231532,0.6588086,0.003862661,0.001084747,0.0008168889,0.003274122,0.004742833,0.07313413,0.001270326,0.003803409,0.2432652],"study_design_scores_gemma":[0.0000334549,0.00535791,0.9377151,0.0002126025,0.0006567955,0.0005006613,0.004788925,0.002386632,0.03477562,0.0004698788,0.01304361,0.00005876583],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762061,0.002302672,0.004043952,0.0002257087,0.00004550685,0.000287658,0.003081329,0.0001103526,0.01369671],"genre_scores_gemma":[0.9859253,0.000847842,0.003193535,0.00008884575,0.00001246632,0.0001812045,0.00127241,0.00002534225,0.008453113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005707723,"threshold_uncertainty_score":0.01909417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02092945802977084,"score_gpt":0.2272009009091018,"score_spread":0.2062714428793309,"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."}}