{"id":"W2115101923","doi":"10.1109/72.963787","title":"Compound binomial processes in neural integration","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Artificial neural network; Computer science; Stochastic process; Bernoulli's principle; Stochastic neural network; Bernoulli process; Event (particle physics); Multiplexing; Bernoulli trial; Algorithm; Mathematics; Artificial intelligence; Recurrent neural network; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009757386,0.0002569437,0.0002188917,0.0001832391,0.0002884209,0.0002381003,0.0006414028,0.0001180937,0.00002442246],"category_scores_gemma":[0.000002794156,0.0002330569,0.00009654952,0.00161774,0.0000659011,0.00072781,0.00000511485,0.0005963556,0.00001967502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000604052,"about_ca_system_score_gemma":0.00002916224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000626582,"about_ca_topic_score_gemma":0.0006469369,"domain_scores_codex":[0.998327,0.00008105535,0.0003843503,0.0005358472,0.0002136821,0.0004581089],"domain_scores_gemma":[0.9990317,0.0002162182,0.0000896682,0.0004580714,0.00007503838,0.0001292774],"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":[0.00004538964,0.0002052319,0.00007194221,0.000004532488,0.000005775923,0.00003721154,0.00007990669,0.8113451,0.0001600792,0.0002566125,0.0003154475,0.1874728],"study_design_scores_gemma":[0.0004231441,0.0001249801,0.0003997759,0.00002554654,0.000006886062,0.0001010374,0.00001137236,0.9973859,0.000462372,0.0001888401,0.0006194786,0.0002506364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09667633,0.0001058793,0.8993728,0.001980836,0.0009466565,0.0003677169,0.000002667545,0.0002791933,0.000267954],"genre_scores_gemma":[0.9975469,0.0001726669,0.0008141996,0.0009059648,0.0002160946,0.0001324658,0.000004650591,0.00001967614,0.0001873984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9008706,"threshold_uncertainty_score":0.9503783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02193154123387744,"score_gpt":0.2515548845564565,"score_spread":0.2296233433225791,"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."}}