{"id":"W2618387153","doi":"10.20982/tqmp.13.2.p105","title":"Spike neural models (part I): The Hodgkin-Huxley model","year":2017,"lang":"en","type":"article","venue":"The Quantitative Methods for Psychology","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Spike (software development); Hodgkin–Huxley model; Neuroscience; Computer science; Artificial intelligence; Biology","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":[0.0002370815,0.0003617813,0.0004425495,0.0002659358,0.0002063792,0.0008768351,0.0007953224,0.0009560338,0.005954721],"category_scores_gemma":[0.0006492603,0.0002185315,0.0004552534,0.0005223627,0.0005441062,0.001197486,0.0005493977,0.0007702037,0.002054885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005440468,"about_ca_system_score_gemma":0.0003989072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002473049,"about_ca_topic_score_gemma":0.001252337,"domain_scores_codex":[0.9999051,0.00002465003,0.000004872187,0.00001872773,0.00003418605,0.00001236343],"domain_scores_gemma":[0.9999226,0.00003039997,0.000009542887,0.000009140749,0.00002120302,0.000007032787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005838366,0.00004053965,0.0007863453,0.0004416362,0.00006130763,0.0001595318,0.0002309729,0.2866202,0.005481089,0.5920662,0.02181648,0.09223741],"study_design_scores_gemma":[0.00001567462,0.00005864905,0.0006869182,0.00009115782,0.0000289004,0.0001258487,0.00004501074,0.6424401,0.001154037,0.3112911,0.04403505,0.00002765783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02775509,0.02114949,0.8156065,0.002533594,0.000941519,0.0001278098,0.00116177,0.001092916,0.1296312],"genre_scores_gemma":[0.7457558,0.0312356,0.110123,0.00142167,0.001063857,0.0004104297,0.001166797,0.0003378045,0.108485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005954721,"threshold_uncertainty_score":0.01992053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3609041974783264,"score_gpt":0.5470005151064314,"score_spread":0.1860963176281051,"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."}}