{"id":"W1487029091","doi":"10.1109/ijcnn.2005.1555863","title":"Differences in the subthreshold dynamics of leaky integrate-and-fire and hodgkin-huxley neuron models","year":2006,"lang":"en","type":"article","venue":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subthreshold conduction; Computer science; Calibration; Biological neuron model; Hodgkin–Huxley model; Spiking neural network; Neuron; Spike (software development); Artificial intelligence; Abstraction; Biological system; Artificial neural network; Mathematics; Physics; Neuroscience; Voltage; Statistics; Biology","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":[0.0007504019,0.00030631,0.0004045789,0.0002280751,0.0002273872,0.0009081392,0.0009255507,0.0008273464,0.001289431],"category_scores_gemma":[0.003467781,0.0003011338,0.0004862709,0.0001748537,0.0004979144,0.00189691,0.0005424814,0.0008777727,0.0002494337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000954362,"about_ca_system_score_gemma":0.0004850011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001812303,"about_ca_topic_score_gemma":0.001376283,"domain_scores_codex":[0.9997652,0.00005738365,0.0000189644,0.00004486089,0.00008341201,0.00003021144],"domain_scores_gemma":[0.9994905,0.0002377477,0.00007015017,0.00007904455,0.00006861846,0.00005388957],"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":[0.0002796173,0.0001152953,0.004180689,0.0001372903,0.00007067031,0.000360258,0.0009442444,0.6571826,0.07149956,0.2433615,0.0008282124,0.02104021],"study_design_scores_gemma":[0.0000162793,0.000054651,0.001770233,0.00001605825,0.00001320298,0.000153526,0.00005763654,0.9499463,0.005356682,0.04182683,0.0007571771,0.0000314211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.643339,0.0008210005,0.3396207,0.001000689,0.00009966888,0.0000848979,0.0002848545,0.0004062523,0.01434288],"genre_scores_gemma":[0.9883232,0.000270821,0.009420558,0.00007093616,0.000006797604,0.00004121814,0.00005328481,0.00004925437,0.001764014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001812303,"threshold_uncertainty_score":0.006924391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0565542515375522,"score_gpt":0.2538402336264336,"score_spread":0.1972859820888814,"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."}}