{"id":"W2005727556","doi":"10.1023/b:abme.0000030238.50895.f0","title":"Stochastic and Coherence Resonance in an In Silico Neural Model","year":2004,"lang":"en","type":"article","venue":"Annals of Biomedical Engineering","topic":"stochastic dynamics and bifurcation","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Stochastic resonance; Coherence (philosophical gambling strategy); Noise (video); Physics; Resonance (particle physics); Coupling (piping); Stochastic process; Stochastic modelling; Nuclear magnetic resonance; Control theory (sociology); Statistical physics; Computer science; Mathematics; Quantum mechanics; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001026695,0.0005757292,0.001326854,0.0008018945,0.000771262,0.001224026,0.001466579,0.003985025,0.002215584],"category_scores_gemma":[0.005160495,0.0008638597,0.0009312202,0.0004580567,0.00192829,0.001618537,0.001379498,0.00138798,0.00018118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001210782,"about_ca_system_score_gemma":0.0008244782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007362256,"about_ca_topic_score_gemma":0.003917828,"domain_scores_codex":[0.9996516,0.0001629971,0.00001818052,0.00005700134,0.000059485,0.000050708],"domain_scores_gemma":[0.9977271,0.001615544,0.0002262244,0.00008411876,0.0001797271,0.0001673184],"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":[0.00004519241,0.00004396255,0.0005214543,0.00002706838,0.00003169489,0.0001430587,0.00007510244,0.9719908,0.00155354,0.0248505,0.0001585283,0.0005590788],"study_design_scores_gemma":[0.000009335758,0.00001192753,0.0001128141,0.00000240229,0.000007443008,0.0000154909,0.000005945135,0.9973797,0.00008382365,0.002328949,0.0000353581,0.000006831378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7773249,0.000508613,0.2002264,0.003436432,0.0002040741,0.00007703773,0.0002920909,0.0003482803,0.01758228],"genre_scores_gemma":[0.9915708,0.0001478196,0.003461536,0.0001306732,0.00003673857,0.00004043058,0.00005703595,0.00003945538,0.004515468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007362256,"threshold_uncertainty_score":0.01463878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983684247802891,"score_gpt":0.2732878997911003,"score_spread":0.2534510573130714,"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."}}