{"id":"W2019134512","doi":"10.1007/s11760-011-0267-z","title":"Enhanced SATD-based cost function for mode selection of H.264/AVC intra coding","year":2011,"lang":"en","type":"article","venue":"Signal Image and Video Processing","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor; Toronto Metropolitan University","funders":"","keywords":"Algorithm; Computer science; Rate–distortion optimization; Computation; Encoder; Coding (social sciences); Context-adaptive binary arithmetic coding; Context-adaptive variable-length coding; Hadamard transform; Mathematical optimization; Mathematics; Statistics; Process (computing); Data compression","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":[0.0003865296,0.000486528,0.0003633571,0.000508406,0.0001870645,0.0004903972,0.0005597298,0.0004189827,0.002736502],"category_scores_gemma":[0.0009828883,0.0001247141,0.0002669936,0.0003305202,0.0001268935,0.0005231829,0.0003973881,0.0004038771,0.0005500916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004221828,"about_ca_system_score_gemma":0.0006365821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002830416,"about_ca_topic_score_gemma":0.005502434,"domain_scores_codex":[0.9997138,0.00005461724,0.00001701468,0.00002206831,0.0001688716,0.00002353489],"domain_scores_gemma":[0.9996111,0.00008536469,0.00001769686,0.00002754669,0.0002460869,0.00001224783],"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":[0.0009297552,0.0002327379,0.001829399,0.0002395654,0.00006849863,0.0001448717,0.00004987941,0.1970283,0.1255009,0.009746047,0.006076438,0.6581535],"study_design_scores_gemma":[0.00001127954,0.00006069245,0.0008026763,0.000008555135,0.00001239869,0.00008945672,0.000007804797,0.9807114,0.01643427,0.0005910273,0.001258222,0.0000123104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05207007,0.0008090082,0.9431906,0.0001630414,0.000116287,0.00005817071,0.000310833,0.0006915611,0.002590438],"genre_scores_gemma":[0.6142145,0.0005102525,0.377436,0.0001066284,0.00006679109,0.000124347,0.001118243,0.0001503969,0.006272887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002830416,"threshold_uncertainty_score":0.009154558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03509553120684467,"score_gpt":0.2746021963152265,"score_spread":0.2395066651083819,"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."}}