{"id":"W3197894387","doi":"10.1126/scirobotics.abk3268","title":"Spiking neural networks take control","year":2021,"lang":"en","type":"letter","venue":"Science Robotics","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Brain Institute","funders":"","keywords":"Artificial neural network; Computer science; Control (management); Architecture; Artificial intelligence; Control engineering; Nervous system network models; Cognitive science; Neuroscience; Types of artificial neural networks; Engineering; Recurrent neural network; Psychology","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":[0.000213816,0.0003086585,0.0003478455,0.0001229238,0.0002889044,0.0001992892,0.0006169883,0.0002670878,0.0000151783],"category_scores_gemma":[0.00007775483,0.0003106882,0.0001029099,0.0006898001,0.0002512934,0.0002465521,0.0001024985,0.002055353,0.000008865183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000115434,"about_ca_system_score_gemma":0.0000514688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.847819e-7,"about_ca_topic_score_gemma":7.109773e-7,"domain_scores_codex":[0.9979162,0.00002655316,0.0002782627,0.0004479015,0.0004364595,0.0008946463],"domain_scores_gemma":[0.9991686,0.0001497124,0.00007023913,0.0004264679,0.0000926613,0.0000923438],"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":[3.858208e-7,0.000001213605,0.00001041059,0.00003475277,0.000005526521,0.0003583074,0.00001142518,0.9735105,0.0005544075,0.00001615908,0.02310912,0.002387757],"study_design_scores_gemma":[0.0001140472,0.00001381044,0.00001702535,0.00008660179,0.00002196996,0.00007394543,0.00000694642,0.972294,0.0003270086,0.00004819295,0.02661138,0.0003850879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.001139099,0.002180829,0.8716162,0.1032108,0.01794025,0.0004523673,0.00001108233,0.001228104,0.002221312],"genre_scores_gemma":[0.3892624,0.00009300454,0.009621897,0.5862817,0.01377684,0.00001082669,0.00005677462,0.000216052,0.000680529],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8619943,"threshold_uncertainty_score":0.9999345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01956692411696083,"score_gpt":0.2312930119900812,"score_spread":0.2117260878731204,"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."}}