{"id":"W2902409051","doi":"10.1007/s11063-018-9955-9","title":"Synthesization of Multi-valued Associative High-Capacity Memory Based on Continuous Networks with a Class of Non-smooth Linear Nondecreasing Activation Functions","year":2018,"lang":"en","type":"article","venue":"Neural Processing Letters","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"National Natural Science Foundation of China","keywords":"Computational intelligence; Class (philosophy); Associative property; Bidirectional associative memory; Content-addressable memory; Computer science; Mathematics; Topology (electrical circuits); Artificial neural network; Pure mathematics; Artificial intelligence; Combinatorics","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":[0.0001178554,0.0002677306,0.0002970137,0.0001627729,0.0002255047,0.0003874722,0.0004741037,0.000303067,0.001671906],"category_scores_gemma":[0.0002423782,0.0001088225,0.0002629654,0.0001985716,0.0002535407,0.0004139125,0.0002904063,0.00031838,0.0001566997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002235694,"about_ca_system_score_gemma":0.0002356251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008585046,"about_ca_topic_score_gemma":0.001986595,"domain_scores_codex":[0.9999502,0.000007604604,0.000004128562,0.00001767715,0.00001270685,0.000007600948],"domain_scores_gemma":[0.9999124,0.00002478996,0.00001146633,0.00001783498,0.00002200795,0.00001149596],"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":[0.0004503811,0.0002404742,0.001045083,0.0003739781,0.0001645516,0.000449067,0.0002106006,0.3981856,0.3096434,0.1165322,0.002209331,0.1704953],"study_design_scores_gemma":[0.00001592704,0.00008826531,0.000254283,0.000008391497,0.0000279118,0.00004530939,0.00001110284,0.9780943,0.01483463,0.005405419,0.001203992,0.00001045663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2453773,0.0008325283,0.7381954,0.0001672683,0.000252825,0.00004533266,0.00008230672,0.0005654256,0.01448166],"genre_scores_gemma":[0.9630182,0.0001216554,0.03495906,0.00003722984,0.00002151088,0.00002759382,0.00003729497,0.00001449525,0.001762998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001671906,"threshold_uncertainty_score":0.005593121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01712823635006667,"score_gpt":0.2301101394175624,"score_spread":0.2129819030674958,"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."}}