{"id":"W2170518693","doi":"10.1109/newcas.2004.1359065","title":"On low power shift register hardware realizations for convolutional encoders and decoders","year":2004,"lang":"en","type":"article","venue":"The 2nd Annual IEEE Northeast Workshop on Circuits and Systems, 2004. NEWCAS 2004.","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Shift register; Computer science; Encoder; Convolutional code; Decoding methods; Field-programmable gate array; Computer hardware; Coding (social sciences); Dissipation; Power (physics); Linear feedback shift register; Algorithm; Parallel computing; Electronic engineering; Chip; Engineering; Mathematics; Telecommunications","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":[0.0001964428,0.0005077726,0.0001837699,0.0004437196,0.0002556247,0.0006436476,0.0005122208,0.0003968478,0.003727537],"category_scores_gemma":[0.0007275701,0.0002564677,0.0002256914,0.0004862433,0.000352202,0.0007941857,0.000261278,0.0007202104,0.0009939048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003417786,"about_ca_system_score_gemma":0.0002839581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003596134,"about_ca_topic_score_gemma":0.001249856,"domain_scores_codex":[0.9997728,0.00005562833,0.00001891796,0.00002684654,0.00009821216,0.00002748028],"domain_scores_gemma":[0.9998191,0.00008882335,0.00002179055,0.00003300331,0.00003075062,0.000006548682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002977577,0.00008239537,0.000491981,0.0005327681,0.00004302065,0.0004500997,0.0002014169,0.05714311,0.1290612,0.4908552,0.005394801,0.3154463],"study_design_scores_gemma":[0.0001645609,0.0009285802,0.001152286,0.0003365543,0.0001170434,0.001503359,0.00009981512,0.4530413,0.2059556,0.2153459,0.1212768,0.00007828096],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06047576,0.003151037,0.9063384,0.0003518041,0.0001902467,0.0001099786,0.0001139618,0.001219542,0.02804918],"genre_scores_gemma":[0.5145974,0.003023614,0.466206,0.0002215242,0.0001733072,0.0001645619,0.0003287865,0.0001600733,0.01512474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003727537,"threshold_uncertainty_score":0.01246983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03053235459895815,"score_gpt":0.2773002132930666,"score_spread":0.2467678586941085,"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."}}