{"id":"W2121925658","doi":"10.1109/ccece.1993.332432","title":"A parallel computer for digital signal processing","year":2002,"lang":"en","type":"article","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Uniprocessor system; Computer science; Synchronization (alternating current); Signal processing; Viterbi decoder; Simple (philosophy); Parallel computing; Digital signal processing; Viterbi algorithm; Fast Fourier transform; Computer hardware; Decoding methods; Algorithm; Multiprocessing; Telecommunications; Channel (broadcasting)","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":[0.0003901089,0.0006226654,0.000466496,0.0006716554,0.0005915603,0.001305819,0.0006129164,0.0009548609,0.01445073],"category_scores_gemma":[0.001030358,0.0001920113,0.0002679193,0.001053548,0.001055044,0.001899779,0.0007426353,0.001609382,0.006401516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006622432,"about_ca_system_score_gemma":0.0005506722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005317699,"about_ca_topic_score_gemma":0.0004607701,"domain_scores_codex":[0.9995162,0.0001588275,0.0000237381,0.00008208977,0.0001930414,0.00002612476],"domain_scores_gemma":[0.9996815,0.000120068,0.00001538374,0.00007671872,0.00008610077,0.00002036624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001116159,0.00005194956,0.0002753546,0.0004839117,0.0000388128,0.0002794186,0.0002039626,0.01002949,0.01315864,0.5807249,0.04940905,0.3452328],"study_design_scores_gemma":[0.00006030056,0.0001558913,0.0003398387,0.0001800745,0.0000257959,0.0008811131,0.00004556871,0.05666699,0.008338299,0.2552454,0.678017,0.00004370073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005615823,0.02510389,0.8853419,0.002726497,0.002154703,0.000195861,0.0002049572,0.00242654,0.0762298],"genre_scores_gemma":[0.1455553,0.0219307,0.7174553,0.001754456,0.002652193,0.0009049383,0.0007462196,0.0005235336,0.1084773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01445073,"threshold_uncertainty_score":0.04834253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02898234321023269,"score_gpt":0.2373961332742753,"score_spread":0.2084137900640426,"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."}}