{"id":"W4304098873","doi":"10.1145/3503161.3547872","title":"Image Quality Assessment: From Mean Opinion Score to Opinion Score Distribution","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 30th ACM International Conference on Multimedia","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mean opinion score; Artificial intelligence; Feature (linguistics); Convolutional neural network; Computer science; Feature extraction; Pattern recognition (psychology); Image quality; Fuzzy logic; Quality (philosophy); Image (mathematics); Fuzzy set; Quality Score; Artificial neural network; Membership function; Sentiment analysis; Data mining; Machine learning; Mathematics; Engineering","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":[0.001357046,0.0007720109,0.0005508392,0.001498188,0.0001920716,0.0009279409,0.0006141242,0.0006817628,0.001147751],"category_scores_gemma":[0.005926399,0.0001889053,0.0005218496,0.0007275101,0.0004378759,0.001471077,0.0006232832,0.0007737826,0.0004104993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007956424,"about_ca_system_score_gemma":0.0002845407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004292853,"about_ca_topic_score_gemma":0.002870871,"domain_scores_codex":[0.9991091,0.0001202414,0.00005525054,0.0002573115,0.0003959482,0.00006220812],"domain_scores_gemma":[0.998252,0.0005211027,0.0002597358,0.0001131065,0.0007838077,0.00007017647],"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":[0.0007577393,0.00017419,0.04303873,0.0003259089,0.0002800349,0.0002118709,0.0003773625,0.126945,0.03184832,0.004945375,0.004607668,0.7864878],"study_design_scores_gemma":[0.00001471814,0.0001248683,0.02033848,0.00003556435,0.00005220303,0.0001428617,0.00005647395,0.9665072,0.007747763,0.003988682,0.0009492704,0.00004184163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1615534,0.00124347,0.8315264,0.0004113193,0.0001154312,0.0001073382,0.0004839357,0.001007821,0.00355091],"genre_scores_gemma":[0.9437275,0.0005971105,0.05362512,0.0000909531,0.00009834815,0.00006428656,0.0004300512,0.00004581323,0.001320738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004292853,"threshold_uncertainty_score":0.008535743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1168967919990316,"score_gpt":0.384707841048861,"score_spread":0.2678110490498294,"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."}}