{"id":"W2927508044","doi":"10.14419/ijet.v7i3.14.16868","title":"DMAIC Six Sigma Methodology in Petroleum Hydrocarbon Oil Classification","year":2018,"lang":"en","type":"article","venue":"International Journal of Engineering & Technology","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"DMAIC; Ishikawa diagram; Control chart; Six Sigma; Principal component analysis; Linear discriminant analysis; Diesel fuel; Cluster analysis; Pareto chart; Environmental science; Petroleum; Fuel oil; Petroleum engineering; Computer science; Statistics; Engineering; Mathematics; Pareto principle; Reliability engineering; Waste management; Operations management; Chemistry; Root cause","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":[0.004847905,0.001367556,0.001268849,0.009114305,0.0007913769,0.002089949,0.001094008,0.0007742145,0.0009940445],"category_scores_gemma":[0.005680238,0.000449571,0.001429264,0.005555433,0.0008990514,0.000745766,0.001011568,0.001285811,0.0005089964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00210882,"about_ca_system_score_gemma":0.003248227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00818119,"about_ca_topic_score_gemma":0.006604494,"domain_scores_codex":[0.995348,0.001297569,0.0004632346,0.0004597779,0.002239549,0.0001918069],"domain_scores_gemma":[0.9954313,0.00131106,0.0007247535,0.0002418968,0.00216506,0.0001259133],"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":[0.0003597038,0.000514887,0.02865626,0.001545018,0.0003980507,0.0001349757,0.0008622722,0.259525,0.02049344,0.02094983,0.001528627,0.665032],"study_design_scores_gemma":[0.00005898624,0.001056529,0.01005157,0.0003628732,0.0001423178,0.000141444,0.0008226156,0.9218317,0.03046969,0.02071198,0.01417826,0.0001720186],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04003241,0.00220368,0.951433,0.0002208631,0.00006896696,0.0003775276,0.0002580436,0.0006704801,0.004734993],"genre_scores_gemma":[0.3823039,0.001509841,0.6122407,0.0001333679,0.0000332971,0.0005265213,0.0008224785,0.00007854288,0.002351289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009114305,"threshold_uncertainty_score":0.02563846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02057798664683179,"score_gpt":0.2687876446433627,"score_spread":0.2482096579965309,"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."}}