{"id":"W2954155227","doi":"10.1109/access.2019.2921003","title":"Building Logistic Spiking Neuron Models Using Analytical Approach","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Spiking neural network; Computer science; Biological neuron model; Artificial neural network; Integrator; Artificial intelligence; Oscillation (cell signaling); Chaotic; Biological system","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":[0.000191569,0.0005384917,0.0004806698,0.0006071751,0.0004062573,0.0006175743,0.0008734106,0.0007911545,0.001694564],"category_scores_gemma":[0.0008479927,0.0003748565,0.0009579874,0.0003756923,0.0004215016,0.0006531806,0.000672863,0.0005473074,0.0005158758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005791556,"about_ca_system_score_gemma":0.000572861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003135228,"about_ca_topic_score_gemma":0.0021692,"domain_scores_codex":[0.999922,0.00001808423,0.000005453708,0.00001459612,0.00002947358,0.00001030947],"domain_scores_gemma":[0.9998739,0.00004488682,0.00002347056,0.0000112442,0.00003808493,0.000008398139],"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":[0.00001723732,0.00002367108,0.0005773048,0.00009998138,0.00002981648,0.0002563488,0.0001275055,0.9090059,0.009434985,0.06875101,0.0006974319,0.01097881],"study_design_scores_gemma":[0.000002020911,0.000005554345,0.0000382113,0.000005815721,0.000003455336,0.00003155234,0.000009414477,0.9903719,0.0003777771,0.008210851,0.0009389743,0.000004366038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03705908,0.0006858111,0.9387889,0.0003227228,0.00007615473,0.00006569119,0.0001445214,0.0002687117,0.02258848],"genre_scores_gemma":[0.7965292,0.002234928,0.1823898,0.0001851615,0.0000809809,0.0004906147,0.0002595735,0.0001928912,0.01763695],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003135228,"threshold_uncertainty_score":0.00623399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1383638562127704,"score_gpt":0.3443878709114669,"score_spread":0.2060240146986966,"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."}}