{"id":"W2141095581","doi":"10.1109/mmsp.2007.4412869","title":"Exponential Decay of Transmission Distortion in H.264","year":2007,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Fading; Residual; Computer science; Transmission (telecommunications); Distortion (music); Frame (networking); Exponential function; Algorithm; Energy (signal processing); Electronic engineering; Statistics; Telecommunications; Mathematics; Bandwidth (computing); Decoding methods; Mathematical analysis; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002645318,0.00004961978,0.0000791009,0.0001614293,0.00002346249,0.00001019164,0.0004021393,0.0000533565,0.00001301952],"category_scores_gemma":[0.000009057702,0.00003862894,0.00003126864,0.0002697317,0.00002123083,0.0001426788,0.00007364332,0.0000632376,0.000003701543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001517123,"about_ca_system_score_gemma":0.00001094712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003234871,"about_ca_topic_score_gemma":0.00001200247,"domain_scores_codex":[0.9993632,0.00001231386,0.0001997288,0.0001456501,0.0001473535,0.0001317761],"domain_scores_gemma":[0.9996468,0.00003412691,0.0000414113,0.0002342569,0.00001766238,0.00002578936],"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":[0.00001213247,0.00007647742,0.001532384,0.000007304064,0.000001272033,0.000006645028,0.0002334213,0.00002520308,0.05550737,0.02611994,0.000148252,0.9163296],"study_design_scores_gemma":[0.0003066318,0.00007308934,0.02007904,0.00005118991,8.959136e-7,0.000003062507,0.0000639891,0.003186246,0.9694921,0.004639568,0.002005741,0.00009841225],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1995736,0.0001055688,0.797412,0.0001825276,0.00008806403,0.00003105943,4.664315e-8,0.0001657898,0.002441369],"genre_scores_gemma":[0.9790733,0.00001573551,0.02074736,0.000014141,0.000005278494,0.000001457383,1.963849e-7,0.000001723876,0.0001408286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9162312,"threshold_uncertainty_score":0.1575242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362069490264646,"score_gpt":0.2522772105661813,"score_spread":0.2386565156635348,"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."}}