{"id":"W4385525205","doi":"10.1109/tetci.2023.3300176","title":"Multiplierless Implementation of Fitz-Hugh Nagumo (FHN) Modeling Using CORDIC Approach","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Emerging Topics in Computational Intelligence","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"CORDIC; Field-programmable gate array; Computer science; Neuromorphic engineering; Virtex; Computer hardware; Hardware description language; Artificial neural network; Computer architecture; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0001533608,0.0001523561,0.0001702018,0.0003450179,0.0001230096,0.0000130923,0.0001430753,0.00005170227,0.00001573634],"category_scores_gemma":[0.000003652753,0.000183576,0.00006877778,0.000743398,0.00002978063,0.0001594793,0.000003187898,0.0002602042,0.000006207958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009084598,"about_ca_system_score_gemma":0.0000235949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003583671,"about_ca_topic_score_gemma":0.0000153059,"domain_scores_codex":[0.9988277,0.00002920234,0.0004632059,0.0002249612,0.0002251569,0.0002298027],"domain_scores_gemma":[0.9995877,0.00014573,0.00004817307,0.0001180159,0.00006338455,0.00003700346],"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":[0.000006049034,0.00002158168,0.00002908621,0.00007405231,0.00001503569,0.000002605747,0.0005889049,0.9609174,0.0008336697,0.0002778392,0.000001365774,0.0372324],"study_design_scores_gemma":[0.0001109469,0.00001693529,0.00005054488,0.00006204743,0.00000779557,0.000004289355,0.000796077,0.9772564,0.0191345,0.002397607,0.000004657101,0.0001582196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3571624,0.00001784092,0.6421535,0.00001635874,0.0003685903,0.0001111,0.000007854629,0.0001291158,0.00003322878],"genre_scores_gemma":[0.9782747,0.00003982956,0.02156449,0.00001565067,0.00004425922,0.00001461974,0.00001014968,0.00002418041,0.00001213466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6211123,"threshold_uncertainty_score":0.7486011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08322204347701156,"score_gpt":0.3532537400759591,"score_spread":0.2700316965989475,"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."}}