{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003568601,0.0005942888,0.0003679598,0.0007059927,0.0004354823,0.0008523327,0.000715028,0.0003221182,0.00930967],"category_scores_gemma":[0.001270414,0.0002651878,0.0003596684,0.000578124,0.0002744513,0.001135278,0.0004170718,0.0007875076,0.0020896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004926348,"about_ca_system_score_gemma":0.0008834629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002140486,"about_ca_topic_score_gemma":0.002635382,"domain_scores_codex":[0.9995183,0.00005745521,0.00003793938,0.00009092405,0.0002516899,0.00004381889],"domain_scores_gemma":[0.9994851,0.0000811938,0.00002850048,0.0001243328,0.0002540247,0.00002680949],"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":[0.0006694696,0.0002292856,0.001779551,0.0002099268,0.00007908828,0.0003092911,0.0002317951,0.03487098,0.1580699,0.03938001,0.01638894,0.7477818],"study_design_scores_gemma":[0.000201989,0.0004162723,0.001430059,0.00003641626,0.00009868305,0.001231317,0.00009484736,0.6321899,0.2755175,0.01209021,0.07662901,0.00006375924],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03172549,0.0003848092,0.927754,0.0002927935,0.0002628802,0.000174254,0.0001464777,0.008241052,0.03101828],"genre_scores_gemma":[0.2079804,0.0005165356,0.763774,0.0001743255,0.0001469402,0.0001447152,0.0005573028,0.0008126342,0.02589317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00930967,"threshold_uncertainty_score":0.03114396,"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."}}