{"id":"W2015172776","doi":"10.1145/1594233.1594307","title":"Power-management-based Chien search for low power BCH decoder","year":2009,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"AUTO21 Network of Centres of Excellence","keywords":"BCH code; Computer science; Decoding methods; Power (physics); Very-large-scale integration; Power analysis; Error detection and correction; Embedded system; Algorithm; Cryptography","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0005635719,0.0001796145,0.0001604198,0.0002517041,0.0001434875,0.0001956827,0.001320118,0.00007259243,0.00007363538],"category_scores_gemma":[0.00002688706,0.000163578,0.0001170996,0.0004750227,0.00002389919,0.0003248804,0.0001605754,0.0001333581,0.00007194107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000667796,"about_ca_system_score_gemma":0.00004937686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001009499,"about_ca_topic_score_gemma":0.000005928317,"domain_scores_codex":[0.9983292,0.00004093197,0.0002204986,0.0005516986,0.0003491229,0.000508515],"domain_scores_gemma":[0.9986803,0.0001188022,0.00004715315,0.0009134286,0.000135399,0.0001049354],"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":[0.0001258084,0.001373875,0.001979516,0.0001071115,0.00009160406,0.00009967207,0.001862553,0.0007042215,0.005798825,0.6107039,0.1138773,0.2632757],"study_design_scores_gemma":[0.004565421,0.004987987,0.02417406,0.0003471472,0.00003700903,0.00004459302,0.0003229286,0.4490525,0.4220093,0.04110195,0.05015515,0.003201954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009828593,0.00001628339,0.9086142,0.00238181,0.0002253674,0.0005646189,9.501035e-7,0.00145351,0.07691468],"genre_scores_gemma":[0.6463423,9.48843e-7,0.3497912,0.002429608,0.00001233477,0.00002474011,0.000001354373,0.00001111333,0.001386414],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6365137,"threshold_uncertainty_score":0.6670519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332962185794859,"score_gpt":0.2909885750240818,"score_spread":0.2776589531661331,"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."}}