{"id":"W2153011871","doi":"10.1109/ccece.1999.808024","title":"Efficient scalable DCT-based video coding","year":2003,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Discrete cosine transform; Computer science; Scalability; Scalable Video Coding; Transform coding; Coding (social sciences); Algorithm; Computer engineering; Theoretical computer science; Artificial intelligence; Mathematics; Image (mathematics)","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":[0.0002548198,0.0003927606,0.0003329844,0.0005196074,0.000218449,0.0004589741,0.0004939632,0.0003319815,0.002474682],"category_scores_gemma":[0.0009894492,0.0001126473,0.00024893,0.0008536238,0.0002302941,0.0006328633,0.0004923905,0.0004838318,0.0009570062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003495524,"about_ca_system_score_gemma":0.0005564213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002280552,"about_ca_topic_score_gemma":0.004183332,"domain_scores_codex":[0.9997104,0.00002466893,0.00001050398,0.00002376858,0.0002092693,0.00002136001],"domain_scores_gemma":[0.9997872,0.00005513776,0.00001798833,0.00003398219,0.00009586922,0.000009953797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001419303,0.00004697236,0.000282792,0.0002655336,0.00002929632,0.0005787021,0.000076403,0.1390043,0.2688617,0.09696633,0.01494833,0.4787977],"study_design_scores_gemma":[0.00002235391,0.00005486784,0.0003032896,0.00003271597,0.00001181878,0.0004894489,0.00002072889,0.92168,0.04249025,0.01261928,0.02225101,0.00002420831],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008850471,0.001094682,0.9785959,0.0001917226,0.0001395265,0.0001008087,0.0002344898,0.0006982062,0.01009425],"genre_scores_gemma":[0.3323514,0.002893609,0.6486404,0.0002285691,0.0002237765,0.0001362024,0.001212061,0.0001482203,0.01416581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002474682,"threshold_uncertainty_score":0.008278668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02021633585333168,"score_gpt":0.2377661862368362,"score_spread":0.2175498503835046,"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."}}