{"id":"W2010876761","doi":"10.1162/08997660151134325","title":"Localist Attractor Networks","year":2001,"lang":"en","type":"article","venue":"Neural Computation","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Attractor; Spurious relationship; Computer science; Statistical physics; Topology (electrical circuits); Theoretical computer science; Mathematics; Physics; Machine learning; Mathematical analysis","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":[0.00005006136,0.0001015898,0.00008388012,0.00004887857,0.0001554226,0.00008782882,0.00008930705,0.00004368028,0.00003862508],"category_scores_gemma":[0.00007052459,0.000091773,0.00004643153,0.0002967294,0.00003918892,0.0002269717,0.00002556477,0.0001460465,0.00005962309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002779418,"about_ca_system_score_gemma":0.000005444591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001366238,"about_ca_topic_score_gemma":0.000007231155,"domain_scores_codex":[0.9991242,0.00007624491,0.0001554726,0.0002755592,0.0001767062,0.0001918259],"domain_scores_gemma":[0.9995904,0.0001637727,0.00007029438,0.00008661493,0.00002854057,0.00006036055],"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":[0.0001699615,0.0001397354,0.002604282,0.00001160715,0.000003223406,0.0001675229,0.00005082208,0.620272,0.1764867,0.004543173,0.002512985,0.193038],"study_design_scores_gemma":[0.0002076528,0.00009350811,0.007735218,0.000003707053,0.000003406218,0.00008865135,0.000003335439,0.9876292,0.001732124,0.0008872329,0.001501553,0.0001144522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9372535,0.00001056524,0.05823212,0.0008594186,0.001106203,0.0001507506,0.000001937605,0.0001917201,0.002193832],"genre_scores_gemma":[0.9972042,0.0000108636,0.00004985925,0.00217825,0.0002167841,0.000004304189,0.00001453229,0.00001386492,0.000307275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3673572,"threshold_uncertainty_score":0.3742394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04136552500281545,"score_gpt":0.2760430936252047,"score_spread":0.2346775686223893,"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."}}