{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025287,0.0001389241,0.0001821111,0.0001655066,0.0002698838,0.0001340886,0.0002700513,0.00008452626,0.000009152536],"category_scores_gemma":[0.00006436415,0.0001232893,0.00004815042,0.0003012203,0.00008224826,0.0007872153,0.00007408177,0.0001226134,0.000001156457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002017208,"about_ca_system_score_gemma":0.00008218098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002076509,"about_ca_topic_score_gemma":0.000003571934,"domain_scores_codex":[0.9990057,0.00003100996,0.0002481254,0.0003442887,0.0001397736,0.0002310689],"domain_scores_gemma":[0.999321,0.00007876222,0.0001943998,0.0001474379,0.0002137947,0.00004458954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008722879,0.00004357531,0.00006971809,0.0001555695,0.000007408431,5.533693e-7,0.0003450115,0.0000326187,0.5045067,0.0009214383,0.0001210831,0.4937091],"study_design_scores_gemma":[0.0003515555,0.0002102218,0.0001249998,0.0001977071,0.00001514306,0.000002629649,0.00009410075,0.1960326,0.7952237,0.007541758,0.00006938083,0.0001362608],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01586354,0.0001637158,0.9829035,0.00007261035,0.00006926047,0.0002154739,0.000001562935,0.0003303528,0.000379932],"genre_scores_gemma":[0.9258588,0.000009312816,0.07388902,0.0001001518,0.00002863674,0.00007434329,0.000001470498,0.000009535333,0.00002872478],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9099953,"threshold_uncertainty_score":0.5027593,"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."}}