{"id":"W1681298107","doi":"10.1023/a:1008135917341","title":"Power and Speed-Efficient Code Transformation of Video Compression Algorithms for RISC Processors","year":2001,"lang":"en","type":"article","venue":"The Journal of VLSI Signal Processing Systems for Signal Image and Video Technology","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"McMaster University","keywords":"Computer science; Video decoder; Cache; Computer hardware; Bandwidth (computing); Software; Data compression; Embedded system; High memory; MPEG-4; Decoding methods; Parallel computing; Operating system; Computer network; Telecommunications; Coding (social sciences)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001252227,0.0003260482,0.0001531845,0.000516607,0.0003335722,0.0003642621,0.0004297001,0.0002246748,0.003352408],"category_scores_gemma":[0.001219473,0.000142679,0.0001681112,0.0006671915,0.000196974,0.000458312,0.0002506676,0.0003563798,0.0008172414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002988999,"about_ca_system_score_gemma":0.0004570802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001161467,"about_ca_topic_score_gemma":0.002415777,"domain_scores_codex":[0.999797,0.00002771793,0.000009747341,0.00001856539,0.0001181318,0.00002874564],"domain_scores_gemma":[0.9995253,0.0001663791,0.00003799693,0.00007749496,0.0001812786,0.00001153192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009305081,0.0001563956,0.001665449,0.0001164487,0.00003430288,0.0001964509,0.0001676217,0.05922064,0.2175873,0.02850613,0.005170227,0.6862486],"study_design_scores_gemma":[0.00008608862,0.0003316887,0.002186586,0.00001796082,0.00003793638,0.0004183037,0.00005493669,0.7167748,0.2626204,0.008976746,0.008472987,0.00002144344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2528829,0.001001675,0.7259703,0.0002814795,0.0001149468,0.0001157669,0.0001420771,0.002856853,0.01663402],"genre_scores_gemma":[0.7675116,0.0003039232,0.2211193,0.0001219606,0.00006235208,0.00008573894,0.0004351466,0.0003858572,0.009974112],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003352408,"threshold_uncertainty_score":0.01121491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02298798773144987,"score_gpt":0.2864760452867369,"score_spread":0.263488057555287,"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."}}