{"id":"W4410023076","doi":"10.1088/2634-4386/add36c","title":"NeuroMorse: a temporally structured dataset for neuromorphic computing","year":2025,"lang":"en","type":"article","venue":"Neuromorphic Computing and Engineering","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Neuromorphic engineering; Computer science; Artificial intelligence; Artificial neural network","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002717799,0.0005413867,0.0005561916,0.0003104901,0.0003655666,0.0001562996,0.0003676805,0.0001318713,0.000003763463],"category_scores_gemma":[0.0002001107,0.000612988,0.0001045798,0.0005466724,0.00005647502,0.000163978,0.0002480852,0.0006772204,0.00000262661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003693624,"about_ca_system_score_gemma":0.00002608875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004183212,"about_ca_topic_score_gemma":0.000001759188,"domain_scores_codex":[0.9977416,0.00004050552,0.0006120934,0.0006710206,0.0001739438,0.000760771],"domain_scores_gemma":[0.9985659,0.0006623231,0.00008371032,0.0004477137,0.00005667588,0.000183641],"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":[0.00003574997,0.0000258974,0.0003739649,0.001178008,0.00008492445,0.0001206352,0.0001356508,0.8857142,0.09122789,0.0008141096,0.002942224,0.01734675],"study_design_scores_gemma":[0.001052071,0.00009754242,0.003410409,0.000293297,0.00005865981,0.0002106874,0.00001751465,0.9763931,0.004608786,0.0001535467,0.0131017,0.0006026606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8501341,0.0005570059,0.1447141,0.0001738523,0.002293554,0.0005510891,0.0001691469,0.001325429,0.00008173743],"genre_scores_gemma":[0.994283,0.00003017032,0.004696028,0.0003500672,0.0003040689,0.000007784196,0.0002007294,0.0001036235,0.00002450894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1441489,"threshold_uncertainty_score":0.9996321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195744381126712,"score_gpt":0.241955470675364,"score_spread":0.2199980268640969,"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."}}