{"id":"W2025967251","doi":"10.1007/s11265-014-0886-z","title":"Algorithm and Architecture of Fully-Parallel Associative Memories Based on Sparse Clustered Networks","year":2014,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Network Packet Processing and Optimization","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Associative property; Field-programmable gate array; Content-addressable memory; Parallel computing; Artificial neural network; Architecture; Content-addressable storage; Computer architecture; Computer hardware; Artificial intelligence; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001529537,0.0002775672,0.0003046792,0.00033149,0.000444928,0.000441831,0.001259703,0.0004477467,0.003015976],"category_scores_gemma":[0.0004215313,0.0001775498,0.0002022623,0.0003912911,0.000200081,0.0005878438,0.0004254804,0.0003179516,0.0003931116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005193073,"about_ca_system_score_gemma":0.001003625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004038173,"about_ca_topic_score_gemma":0.007279957,"domain_scores_codex":[0.9999348,0.00001079933,0.000004492063,0.00001550339,0.00002246601,0.00001193027],"domain_scores_gemma":[0.9998595,0.0000269757,0.00001078705,0.00001864638,0.00007544138,0.000008640085],"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":[0.0002557076,0.00008787913,0.001212788,0.0001735477,0.00007069534,0.00009591714,0.0000995986,0.7105182,0.01995068,0.03321225,0.005177896,0.2291448],"study_design_scores_gemma":[0.00001925968,0.00003532547,0.0001195175,0.00000476522,0.0000124836,0.00004055113,0.00001485545,0.9902845,0.003706704,0.004907191,0.0008494032,0.00000538102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06960386,0.0003015718,0.9204635,0.0002824319,0.00008089185,0.0001310015,0.0001359246,0.0009842989,0.00801647],"genre_scores_gemma":[0.5556983,0.0002429694,0.4365272,0.0001116693,0.00003498163,0.0002555983,0.0003056673,0.00006576732,0.006757789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004038173,"threshold_uncertainty_score":0.0100894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00867406844215649,"score_gpt":0.2171119082575264,"score_spread":0.2084378398153699,"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."}}