{"id":"W4400233807","doi":"10.1109/iscas58744.2024.10558124","title":"NURODE: In-Memory Crossbar Core for Hodgkin-Huxley Model ODE-Based Computations","year":2024,"lang":"en","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Computation; Ode; Crossbar switch; Computer science; Core (optical fiber); Parallel computing; Applied mathematics; Mathematics; Algorithm; 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":[0.0002275147,0.0004268603,0.0004287,0.0002595757,0.0002669941,0.0005359176,0.001179011,0.0004525397,0.01215573],"category_scores_gemma":[0.0008558999,0.0002536903,0.0003861825,0.0002197402,0.0002110933,0.0007455038,0.0007878735,0.0008061454,0.002845647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002914612,"about_ca_system_score_gemma":0.0005659371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001382065,"about_ca_topic_score_gemma":0.002072199,"domain_scores_codex":[0.9999036,0.00001890795,0.000006706593,0.00001620259,0.00004221649,0.00001244762],"domain_scores_gemma":[0.9998457,0.00004827584,0.0000106974,0.00003229725,0.00005153119,0.00001143162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002228672,0.0002140813,0.001320504,0.0007377426,0.0001534104,0.0003453935,0.000350967,0.5449772,0.05044413,0.1281106,0.01022364,0.2628994],"study_design_scores_gemma":[0.00001446263,0.00002268158,0.0000753974,0.00001599443,0.000009813556,0.00004559327,0.00001451124,0.9751356,0.01047814,0.00679775,0.007382551,0.000007500629],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0141365,0.000178815,0.9741401,0.00007468164,0.00006736649,0.00003293815,0.0001214223,0.003401743,0.007846422],"genre_scores_gemma":[0.3156503,0.0004307586,0.6689959,0.0001299149,0.00003593643,0.0002461404,0.0004417887,0.001131836,0.01293738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01215573,"threshold_uncertainty_score":0.04066503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04746155628336122,"score_gpt":0.3277094437939863,"score_spread":0.2802478875106251,"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."}}