{"id":"W2768333611","doi":"10.1109/tcsii.2017.2695531","title":"A Fully Serial-In Parallel-Out Digit-Level Finite Field Multiplier in $\\mathbb {F}_{2^{m}}$ Using Redundant Representation","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits & Systems II Express Briefs","topic":"Cryptography and Residue Arithmetic","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Finite field; Numerical digit; Multiplier (economics); Representation (politics); Arithmetic; Mathematics; Field (mathematics); Computer science; Discrete mathematics; Pure mathematics","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":[0.0004244203,0.0003512609,0.0005262651,0.0005778888,0.0009162314,0.0008603198,0.001275156,0.0002668932,0.0000103465],"category_scores_gemma":[0.00005928535,0.0003609716,0.0002204023,0.0003972644,0.0001128195,0.001440947,0.00002535159,0.0004788435,0.00001889723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001228712,"about_ca_system_score_gemma":0.0001510141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004425081,"about_ca_topic_score_gemma":0.001164011,"domain_scores_codex":[0.9968566,0.0002449455,0.0008282169,0.0009269419,0.0005283388,0.0006149689],"domain_scores_gemma":[0.9972038,0.0003698787,0.0003642043,0.001796065,0.0001023708,0.0001636418],"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":[0.0003172817,0.002320232,0.003397926,0.0005841454,0.0003112335,0.0009147451,0.03536215,0.7567372,0.09245426,0.003304637,0.0003768514,0.1039193],"study_design_scores_gemma":[0.02316589,0.001399091,0.04146621,0.008927247,0.0002246052,0.0007176572,0.002470483,0.7315997,0.1738318,0.003571236,0.006733006,0.005893022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1354863,0.0001010143,0.8597034,0.0002551628,0.002836532,0.0008120276,0.0000386653,0.0001303439,0.0006365163],"genre_scores_gemma":[0.9970067,0.00005369073,0.002014049,0.00007267744,0.0001256512,0.0001906482,0.00000206092,0.00003182908,0.0005027137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8615203,"threshold_uncertainty_score":0.9998842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07022816247133805,"score_gpt":0.2988033030352079,"score_spread":0.2285751405638698,"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."}}