{"id":"W2613860934","doi":"","title":"Neural Synchrony Through Controlled Tracking","year":2001,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Information processing; Computer science; Spike (software development); Consciousness; Neural engineering; Spike train; Cognitive science; Neural decoding; Artificial intelligence; Psychology; Neuroscience; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003931588,0.0003242757,0.0003500249,0.0002891838,0.0004126848,0.0007689258,0.0008398324,0.0006656002,0.002100153],"category_scores_gemma":[0.001573364,0.0001986278,0.0004515548,0.0002650814,0.0008863275,0.001335659,0.0009540079,0.0005886307,0.0003790339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006600854,"about_ca_system_score_gemma":0.0003900818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001692618,"about_ca_topic_score_gemma":0.001022555,"domain_scores_codex":[0.9997917,0.00004073295,0.00001036482,0.00006504148,0.00006480849,0.00002737546],"domain_scores_gemma":[0.9995963,0.0001440925,0.00007781834,0.00008637363,0.00003929556,0.00005610478],"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":[0.0001418893,0.00006152387,0.0007117689,0.0000483995,0.00003908682,0.0003074952,0.0001918217,0.5988203,0.02794459,0.3437455,0.001118657,0.02686901],"study_design_scores_gemma":[0.00002210685,0.00003172419,0.0001288019,0.000003358047,0.000007339169,0.00004052512,0.000006127101,0.9513107,0.001500534,0.04575756,0.001182776,0.000008409777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1119161,0.0002354348,0.8647033,0.0004164931,0.0001101343,0.00005227846,0.00009112152,0.0006497964,0.0218254],"genre_scores_gemma":[0.9685792,0.0001671269,0.0250363,0.00004396923,0.00003223122,0.00008476706,0.00004396302,0.00004673925,0.005965774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002100153,"threshold_uncertainty_score":0.007025659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02755593753318841,"score_gpt":0.2365458620985315,"score_spread":0.208989924565343,"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."}}