{"id":"W2804100647","doi":"10.5539/cis.v11n3p1","title":"A Bayesian Network Based Method for Service Quality Optimization","year":2018,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Context (archaeology); Bayesian network; Service (business); Quality (philosophy); Set (abstract data type); Service quality; Quality assurance; The Internet; Quality of service; Quality of experience; Bayesian probability; Video quality; Fuzzy logic; Data mining; Machine learning; Artificial intelligence; World Wide Web; Computer network; Metric (unit); Operations management","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":[],"consensus_categories":[],"category_scores_codex":[0.002658793,0.00009774676,0.0001185054,0.0001449135,0.0005947024,0.0009172727,0.0006716845,0.00003271355,0.000005402926],"category_scores_gemma":[0.00005023892,0.0000874651,0.00002681255,0.001152569,0.0001125382,0.009108293,0.0002500638,0.00004448499,0.00001150512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003338517,"about_ca_system_score_gemma":0.0002310344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001949786,"about_ca_topic_score_gemma":0.0000018977,"domain_scores_codex":[0.9987074,0.00006932229,0.0003595549,0.0002349164,0.0003468507,0.0002819588],"domain_scores_gemma":[0.9983518,0.0001547852,0.0001674721,0.000373319,0.0008405027,0.0001121358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002974457,0.00004576021,0.0002107307,0.0001565671,0.000009027972,1.62531e-7,0.005212116,0.1837143,0.00008221253,0.369256,0.00278901,0.4384944],"study_design_scores_gemma":[0.0003196461,0.0001009263,0.001699081,0.00001457633,0.000001857529,0.000002504695,0.00001923653,0.9882212,0.0003607052,0.001148256,0.00798156,0.0001304086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008285917,0.000004081003,0.9956585,0.002110258,0.0004557276,0.0002472339,0.000002316683,0.0001004858,0.001338577],"genre_scores_gemma":[0.02960415,0.00000141363,0.952572,0.01762647,0.0001673585,0.00001611546,0.000006701523,0.00000178606,0.000003995351],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.804507,"threshold_uncertainty_score":0.8845282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03547636515820929,"score_gpt":0.3669422895748985,"score_spread":0.3314659244166892,"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."}}