{"id":"W2116494657","doi":"10.1162/08997660360675035","title":"Analytic Expressions for Rate and CV of a Type I Neuron Driven by White Gaussian Noise","year":2003,"lang":"en","type":"article","venue":"Neural Computation","topic":"stochastic dynamics and bifurcation","field":"Physics and Astronomy","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"White noise; Biological neuron model; Gaussian noise; Mathematics; Noise (video); Gaussian; Multiplicative function; Statistical physics; Mathematical analysis; Applied mathematics; Algorithm; Physics; Statistics; Artificial neural network; Computer science; Artificial intelligence; Quantum mechanics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009084464,0.0006707783,0.0006424338,0.0007220729,0.0003495589,0.0009457515,0.001352918,0.001043986,0.001904722],"category_scores_gemma":[0.003148508,0.0003144032,0.0008619258,0.0004649242,0.001272765,0.0009855687,0.0006950818,0.0008342575,0.0003351906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055043,"about_ca_system_score_gemma":0.000722606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002986098,"about_ca_topic_score_gemma":0.001297038,"domain_scores_codex":[0.9998467,0.00004964523,0.00000964703,0.00002883361,0.00003969778,0.00002545062],"domain_scores_gemma":[0.9990947,0.0004011124,0.0001802658,0.00005422718,0.0001792892,0.000090406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004714192,0.00002504947,0.001778981,0.0001710778,0.0000548112,0.0004954333,0.0004388005,0.7291965,0.01859617,0.2439244,0.0008310448,0.0044405],"study_design_scores_gemma":[0.000003016818,0.000009953246,0.0001770985,0.00001122516,0.000007016092,0.00005372204,0.00002075525,0.981487,0.0002962474,0.01779192,0.0001315743,0.00001059469],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3406813,0.001327399,0.6356562,0.001040492,0.0001084161,0.00006673236,0.0002121361,0.0003851708,0.02052204],"genre_scores_gemma":[0.9764069,0.0008043948,0.01650354,0.00008379468,0.00004404596,0.00008736309,0.0001026115,0.0001314831,0.005835918],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002986098,"threshold_uncertainty_score":0.007654965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01172094551741481,"score_gpt":0.2620758549645966,"score_spread":0.2503549094471818,"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."}}