{"id":"W2139978841","doi":"10.1109/tcsvt.2011.2138770","title":"Rate-Distortion Optimized Pixel-Based Motion Vector Concatenation for Reference Picture Selection","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems for Video Technology","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Motion vector; Concatenation (mathematics); Computer science; Artificial intelligence; Distortion (music); Pixel; Video quality; Transcoding; Selection (genetic algorithm); Motion estimation; Rate–distortion optimization; Computer vision; Block-matching algorithm; Pattern recognition (psychology); Algorithm; Video processing; Video tracking; Mathematics; Image (mathematics); Telecommunications; Bandwidth (computing)","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":[0.0006883689,0.0006416332,0.0005440302,0.0004669001,0.0002387176,0.0005017613,0.0006618179,0.0003352817,0.001389861],"category_scores_gemma":[0.002084577,0.0001978113,0.0002281329,0.0006682351,0.000233033,0.0008128304,0.0004256757,0.0005178551,0.0004347403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003199217,"about_ca_system_score_gemma":0.000519368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000864287,"about_ca_topic_score_gemma":0.001541159,"domain_scores_codex":[0.9993939,0.000156392,0.00004442859,0.00008841701,0.0002827957,0.00003396843],"domain_scores_gemma":[0.999255,0.0002613793,0.0001068531,0.0001616873,0.0001915367,0.00002348397],"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":[0.0006018743,0.00008488228,0.001071872,0.0001541241,0.00007746278,0.0001908439,0.000124343,0.1033522,0.1907166,0.01918991,0.003613025,0.6808228],"study_design_scores_gemma":[0.00003788869,0.0003073751,0.0009292052,0.00001451179,0.00003530681,0.000548377,0.00002618622,0.8482041,0.1408465,0.002712719,0.006296312,0.00004139986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02231411,0.0006491739,0.9752644,0.00005748256,0.00003648772,0.00004082013,0.00005558653,0.0007094531,0.00087243],"genre_scores_gemma":[0.3106021,0.0005668562,0.6855689,0.00005460505,0.00006658315,0.00007689613,0.0002925033,0.0001212375,0.002650327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001389861,"threshold_uncertainty_score":0.00464952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05885655333958575,"score_gpt":0.2556613700777854,"score_spread":0.1968048167381996,"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."}}