{"id":"W2133587528","doi":"10.1109/asic.1998.722897","title":"Implementation and trade-offs of a DCT architecture using high-level synthesis","year":2002,"lang":"en","type":"article","venue":"","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Discrete cosine transform; Computer science; High-level synthesis; Latency (audio); Computer architecture; Overhead (engineering); Architecture; Throughput; Multiplexing; Critical path method; Embedded system; Computer engineering; Parallel computing; Field-programmable gate array; Artificial intelligence; Engineering; Operating system","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":[0.0006751749,0.0005103576,0.0002573286,0.0003462656,0.0003155052,0.0006926747,0.0007107113,0.000409271,0.002611126],"category_scores_gemma":[0.001799625,0.0002202178,0.0003279577,0.0002669929,0.0003147385,0.0009395128,0.0003893414,0.0004879062,0.0003024531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005903704,"about_ca_system_score_gemma":0.0005885418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008572388,"about_ca_topic_score_gemma":0.001454622,"domain_scores_codex":[0.9992478,0.0001759537,0.00005394682,0.00006778019,0.0003422643,0.0001122766],"domain_scores_gemma":[0.9990452,0.0004421445,0.00008595255,0.0001872589,0.0002014342,0.00003800372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001134901,0.0002402637,0.001889345,0.0002604903,0.0001129834,0.0004654946,0.0001545385,0.2524405,0.4258269,0.02180208,0.001117384,0.2945552],"study_design_scores_gemma":[0.0001851596,0.001704695,0.001785475,0.00002813916,0.0001093183,0.0005643324,0.00006331945,0.7284183,0.2527122,0.006550986,0.007845096,0.0000329029],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3880333,0.0006195498,0.5907456,0.0002682344,0.00006971857,0.0001701169,0.00005816034,0.001949889,0.01808545],"genre_scores_gemma":[0.883283,0.0001046648,0.1146839,0.00004421123,0.00002024605,0.00003846887,0.00004669503,0.00008970385,0.001689047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002611126,"threshold_uncertainty_score":0.00873512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06418893512920011,"score_gpt":0.287420540473004,"score_spread":0.2232316053438039,"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."}}