{"id":"W9658607","doi":"","title":"H.264/SVCにおける適応的GOPサイズを用いた符号化効率改善手法の検討 (第21回 回路とシステム軽井沢ワークショップ論文集) -- (動画像符号化(1))","year":2008,"lang":"en","type":"article","venue":"回路とシステム軽井沢ワークショップ論文集","topic":"Hepatitis C virus research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005359912,0.0003233878,0.0002810658,0.0002806021,0.0003780017,0.0003981645,0.000136235,0.000221225,0.003930119],"category_scores_gemma":[0.0003125988,0.0001453676,0.0001806961,0.0002145137,0.0004306734,0.0001049959,0.0001275779,0.0003522539,0.001532261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004338238,"about_ca_system_score_gemma":0.0003898896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01010393,"about_ca_topic_score_gemma":0.009017493,"domain_scores_codex":[0.9997867,0.00003182984,0.00001915437,0.00002271113,0.00006624982,0.00007336838],"domain_scores_gemma":[0.9997407,0.0000516806,0.00006781725,0.00002251059,0.00005366424,0.00006372068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005492509,0.001260516,0.2906103,0.0003782243,0.0001581988,0.004018432,0.0003227446,0.0004970755,0.6273463,0.0009678466,0.01005598,0.05889186],"study_design_scores_gemma":[0.0007338319,0.01477845,0.663892,0.0002904203,0.0002069444,0.01344916,0.0006649624,0.002148087,0.2631904,0.0003583323,0.04021168,0.00007570143],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9904327,0.002088771,0.0006887551,0.0002649362,0.0001842634,0.0001726471,0.001009565,0.00003849397,0.005119985],"genre_scores_gemma":[0.9866359,0.002804491,0.001936971,0.0004583305,0.0002888506,0.00006801293,0.002497402,0.00002212044,0.005287869],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01010393,"threshold_uncertainty_score":0.02009028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1069838638142436,"score_gpt":0.357077089275435,"score_spread":0.2500932254611914,"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."}}