{"id":"W2374171761","doi":"","title":"Video Encoder and Decoder’s Parallelization Based on Parallel Studio","year":2010,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Encoder; Multi-core processor; Parallel computing; Videoconferencing; Studio; Computer hardware; Multimedia; Operating system; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001311832,0.0001777149,0.0001503083,0.0001718516,0.0003281452,0.0002287263,0.0009478169,0.0001171394,0.000007678298],"category_scores_gemma":[0.000003155275,0.0001592321,0.00004692511,0.0003218514,0.00007531049,0.0001635622,0.000319546,0.0002731201,0.00006965307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001317137,"about_ca_system_score_gemma":0.00003876291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005272366,"about_ca_topic_score_gemma":0.000009375976,"domain_scores_codex":[0.99879,0.00002617102,0.0002198636,0.0005741875,0.0001600908,0.000229732],"domain_scores_gemma":[0.998814,0.0001298574,0.00008278062,0.0008089641,0.00008219506,0.00008222937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006905638,0.0003596569,0.001890451,0.000024913,0.00002064262,0.0000029653,0.0002665484,0.00383329,0.01302706,0.1604846,0.01386232,0.8062207],"study_design_scores_gemma":[0.0009238011,0.0001018374,0.007124688,0.00003276292,0.00001170515,0.00002551614,0.00001585632,0.4193214,0.007008874,0.0278405,0.5370243,0.0005687183],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003756146,0.00006477672,0.990783,0.00352826,0.00004717143,0.0004170201,0.000002097109,0.000756454,0.0006450554],"genre_scores_gemma":[0.3701356,0.00001931593,0.6280645,0.001174833,0.00006147233,0.0004410072,0.000005874602,0.00001063139,0.00008675447],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.805652,"threshold_uncertainty_score":0.6493297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008677605493277158,"score_gpt":0.240456313308565,"score_spread":0.2317787078152878,"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."}}