{"id":"W4392615529","doi":"10.1038/s41598-024-55784-1","title":"Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Calgary","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Division of Emerging Frontiers in Research and Innovation; Consejo Nacional de Ciencia y Tecnología; National Institutes of Health; National Science Foundation","keywords":"Neuromorphic engineering; Computer science; Spiking neural network; Realization (probability); Memristor; Electrical element; Electronic circuit; Electric fish; Artificial neural network; Topology (electrical circuits); Neuroscience; Electronic engineering; Physics; Artificial intelligence; Mathematics; Fish <Actinopterygii>","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004520947,0.0001191353,0.00008613751,0.0001133637,0.0002129113,0.000193371,0.00003308073,0.00003001243,0.0001010219],"category_scores_gemma":[0.00009958947,0.0001146218,0.00003041972,0.0003931556,0.00008300549,0.0003855937,0.00003513107,0.0002243816,0.0000189286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002360932,"about_ca_system_score_gemma":0.00002785167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.605323e-7,"about_ca_topic_score_gemma":7.584521e-7,"domain_scores_codex":[0.9985955,0.00001818607,0.000274887,0.0006352345,0.0002806621,0.0001955623],"domain_scores_gemma":[0.9995324,0.00004367681,0.00003760522,0.0002560791,0.00006052163,0.00006971837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003684242,0.00005742522,0.002391175,0.0004381452,0.0001389952,0.002278803,0.0004662715,0.06930273,0.8358983,0.0005543411,0.037203,0.05123396],"study_design_scores_gemma":[0.0003429227,0.000234873,0.01804141,0.0003775259,0.0001554525,0.005472231,0.0001335004,0.21352,0.1744852,0.03357632,0.5525942,0.001066394],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9695197,0.000455644,0.007525869,0.00006401003,0.02050031,0.0001649574,0.000003798322,0.0005745618,0.001191179],"genre_scores_gemma":[0.9982679,0.000008077561,0.0001957585,0.00002464504,0.0002610438,0.000009788378,0.00003011203,0.00002186115,0.001180845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6614131,"threshold_uncertainty_score":0.4674141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01986855042110296,"score_gpt":0.2317475058536019,"score_spread":0.211878955432499,"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."}}