{"id":"W2164264252","doi":"10.1109/biocas.2010.5709557","title":"A phase synchronization and magnitude processor VLSI architecture for adaptive neural stimulation","year":2010,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Very-large-scale integration; CMOS; Computer science; Synchronization (alternating current); Throughput; Computer hardware; Electronic engineering; Channel (broadcasting); Embedded system; Engineering; Wireless; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.00005285546,0.0001001509,0.000079593,0.0000547532,0.0001134305,0.00009162952,0.00009949627,0.00004511945,0.00002762596],"category_scores_gemma":[0.0002077149,0.00007613494,0.00001983001,0.00009206099,0.00006389914,0.0001858822,0.00003254094,0.0001213633,0.000002761428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004489421,"about_ca_system_score_gemma":0.00001609128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003474293,"about_ca_topic_score_gemma":0.00003662332,"domain_scores_codex":[0.9993451,0.00001997106,0.0001072153,0.0002863651,0.00009634629,0.0001449498],"domain_scores_gemma":[0.9995596,0.0002038059,0.00004754151,0.00008510046,0.00005382321,0.00005005966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001803039,0.0002251478,0.00009913189,0.00005019953,0.000003206557,0.000002274398,0.0007862141,0.001470329,0.8602328,0.001810696,0.0002540968,0.1348857],"study_design_scores_gemma":[0.001595987,0.0006715572,0.0001998804,0.000008692013,0.000008799651,0.00002917685,0.00002079671,0.6442135,0.3508177,0.00153345,0.0007624908,0.0001380233],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8211983,0.000006529913,0.1772176,0.0005711513,0.0001602076,0.0004376904,0.00001376937,0.00009049181,0.0003041915],"genre_scores_gemma":[0.992391,6.432151e-7,0.006632899,0.0005447696,0.0001162809,0.00001829407,0.000004482108,0.00001101262,0.0002805896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6427432,"threshold_uncertainty_score":0.3104693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251241441647985,"score_gpt":0.3037591945050935,"score_spread":0.278635050340295,"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."}}