{"id":"W2791497415","doi":"10.1109/icip.2017.8296928","title":"Perceptual aliasing factors and the impact of frame rate on video quality","year":2017,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Aliasing; Computer science; Frame rate; Computer vision; Frame (networking); Video quality; Perception; Artificial intelligence; Residual frame; Quality (philosophy); Reference frame; Telecommunications; Engineering; Psychology; Filter (signal processing)","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":[0.001419929,0.0006763584,0.000337473,0.001193818,0.000210221,0.0007350246,0.0003220798,0.0004865329,0.001010913],"category_scores_gemma":[0.0143718,0.000181001,0.000350671,0.000715499,0.0005243431,0.001294954,0.0003770699,0.0004836372,0.0001929446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003416844,"about_ca_system_score_gemma":0.0002640364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002337498,"about_ca_topic_score_gemma":0.001614694,"domain_scores_codex":[0.9985712,0.0004050415,0.00008778471,0.0001951489,0.0006386854,0.00010227],"domain_scores_gemma":[0.9880201,0.007893004,0.001451274,0.0006992893,0.001746482,0.0001898259],"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":[0.002847119,0.0004882297,0.06951784,0.0008458159,0.0003082288,0.001004932,0.0005584577,0.1126166,0.3542197,0.003548082,0.001059134,0.452986],"study_design_scores_gemma":[0.00004986898,0.001961908,0.2172228,0.00009750426,0.0004566607,0.001506179,0.000363257,0.5688465,0.2036807,0.003487599,0.002140566,0.0001864803],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6815282,0.003376877,0.3098344,0.0001626193,0.0001001499,0.0001174083,0.0002107249,0.0003611677,0.004308386],"genre_scores_gemma":[0.9772602,0.0009486158,0.02112905,0.0000322537,0.00004529791,0.00001946202,0.0001117769,0.00004181784,0.0004114386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002337498,"threshold_uncertainty_score":0.00750941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09200584726176331,"score_gpt":0.4203566460942756,"score_spread":0.3283507988325123,"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."}}