{"id":"W2964213580","doi":"","title":"Subjective and Objective Quality Assessment of Image: A Survey","year":2014,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Image quality; Distortion (music); Feature (linguistics); Quality (philosophy); Artificial intelligence; Computer science; Fidelity; Similarity (geometry); Range (aeronautics); Pattern recognition (psychology); Image processing; Measure (data warehouse); Data mining; Quality Score; Computer vision; Image (mathematics); Metric (unit); 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01029915,0.0003564048,0.001145377,0.0005807077,0.0002588384,0.001715616,0.003642377,0.0001051616,0.0004116847],"category_scores_gemma":[0.001122554,0.0003232661,0.0001848706,0.001224387,0.0002766683,0.004851248,0.002470762,0.0004652849,0.000003845626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001491845,"about_ca_system_score_gemma":0.0004196735,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007296718,"about_ca_topic_score_gemma":0.0003373651,"domain_scores_codex":[0.9933162,0.003139584,0.001243507,0.0007556019,0.001104738,0.0004403459],"domain_scores_gemma":[0.9938618,0.002188909,0.001526465,0.001002337,0.001152864,0.0002676538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001034243,0.0006339644,0.9170801,0.0001886745,0.0002999663,0.00001084979,0.000910497,0.00003424857,0.04545433,0.007115659,0.002585891,0.02558237],"study_design_scores_gemma":[0.0006322555,0.00004264792,0.9582309,0.0001412973,0.00002803337,0.000006653809,0.0001060998,0.001324797,0.02126437,0.01764921,0.0001950171,0.0003787345],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6107758,0.001488475,0.378222,0.0002584999,0.0004871965,0.0006423728,0.00006700643,0.00005133677,0.008007376],"genre_scores_gemma":[0.9890903,0.0007882085,0.009625465,0.0002866932,0.00006581847,0.00003125344,0.00000726072,0.0000238502,0.00008112356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3783146,"threshold_uncertainty_score":0.9999219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3237018083929355,"score_gpt":0.610291719362176,"score_spread":0.2865899109692405,"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."}}