{"id":"W1986464974","doi":"10.1016/j.compeleceng.2012.12.009","title":"Dynamic partial reconfigurable Viterbi decoder for wireless standards","year":2013,"lang":"en","type":"article","venue":"Computers & Electrical Engineering","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Viterbi decoder; Control reconfiguration; Throughput; Embedded system; Code (set theory); Wireless; Viterbi algorithm; Computer hardware; Computer architecture; Parallel computing; Decoding methods; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001320877,0.0002720623,0.0003336383,0.0001790089,0.00007161265,0.00009381276,0.0004171419,0.0001303191,0.00002353083],"category_scores_gemma":[0.00004773419,0.0003045352,0.0001071403,0.0003276701,0.00001894073,0.0003034154,0.00003482755,0.0003150321,0.00001237838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000392756,"about_ca_system_score_gemma":0.00002895497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004220442,"about_ca_topic_score_gemma":0.000001053317,"domain_scores_codex":[0.998587,0.00001306829,0.0003615319,0.000245588,0.0002258479,0.0005669469],"domain_scores_gemma":[0.9989899,0.0002490623,0.00003601941,0.0004265781,0.000147168,0.0001512279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001247671,0.00004341233,0.00001397832,0.0001789804,0.0001114363,0.000002465088,0.0000919628,0.5153795,0.1303435,0.001833928,0.009531407,0.342457],"study_design_scores_gemma":[0.0002750924,0.00005599697,0.00006332281,0.00004863404,0.000007680899,0.000007078843,0.00000158842,0.9525474,0.03328503,0.0003105424,0.01304673,0.0003508847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01568586,0.0006678117,0.9803218,0.00008362759,0.0003787632,0.000553936,0.00001033182,0.002091787,0.0002061304],"genre_scores_gemma":[0.8985537,0.0001851747,0.1005071,0.00005719448,0.00005909264,0.0004761081,0.00001964704,0.0001104824,0.00003161035],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8828678,"threshold_uncertainty_score":0.9999407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005453007453183952,"score_gpt":0.2286766248023578,"score_spread":0.2232236173491739,"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."}}