{"id":"W3160337074","doi":"10.1109/icassp39728.2021.9413898","title":"Real Versus Fake 4k - Authentic Resolution Assessment","year":2021,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Frame (networking); Image resolution; Resolution (logic); Construct (python library); Computer vision; Superresolution; Image (mathematics); Pattern recognition (psychology)","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":[0.001684422,0.0007724355,0.001019211,0.002365079,0.0003316224,0.001244178,0.001006478,0.0009156134,0.003529104],"category_scores_gemma":[0.006131042,0.0002429332,0.0006272096,0.001030198,0.0004576831,0.001540252,0.001006793,0.0005594483,0.002677631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005670065,"about_ca_system_score_gemma":0.0002844876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001966077,"about_ca_topic_score_gemma":0.002597582,"domain_scores_codex":[0.9978408,0.0003492215,0.0001433212,0.0004648972,0.001034733,0.0001670179],"domain_scores_gemma":[0.9970084,0.0006536123,0.000440748,0.0009039752,0.0008822139,0.0001111079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002059873,0.0004046923,0.0364831,0.0009101014,0.000251854,0.0007383266,0.0002195576,0.03594283,0.0765551,0.002443391,0.01042319,0.8335679],"study_design_scores_gemma":[0.00006750909,0.0006854968,0.08507564,0.0001334017,0.0001967836,0.003667243,0.0004273706,0.6265444,0.2586104,0.00452077,0.01991199,0.0001589316],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.674367,0.003799025,0.2951965,0.0004077681,0.0002828585,0.000641293,0.005239792,0.006833359,0.01323251],"genre_scores_gemma":[0.8672286,0.0009296651,0.1198351,0.000123699,0.00007923958,0.0001258627,0.005849166,0.0002267695,0.00560179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003529104,"threshold_uncertainty_score":0.01180601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05176358954835644,"score_gpt":0.3644165587193787,"score_spread":0.3126529691710223,"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."}}