{"id":"W2195130835","doi":"","title":"BAM Learning in High Level of Connection Sparseness.","year":2014,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Curse of dimensionality; Computer science; Artificial intelligence; Recall; Convergence (economics); Artificial neural network; Associative property; Machine learning; Connection (principal bundle); Content-addressable memory; Associative learning; Mathematics; Cognitive psychology; Psychology","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":[0.001488104,0.0003732021,0.0008708473,0.0004197131,0.0003872163,0.001031404,0.00107528,0.001021858,0.002289397],"category_scores_gemma":[0.01272712,0.0004373467,0.0005023135,0.0004236812,0.001257025,0.002874981,0.001388228,0.00145563,0.0003337077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007301808,"about_ca_system_score_gemma":0.0004945476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001176779,"about_ca_topic_score_gemma":0.001530591,"domain_scores_codex":[0.9995209,0.0001798403,0.00002773055,0.0001034476,0.0001051146,0.00006296075],"domain_scores_gemma":[0.9945258,0.003523605,0.0005995681,0.0006750943,0.0004700834,0.0002059304],"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":[0.0003452613,0.0001401699,0.004821183,0.0003924011,0.0001588197,0.0004142377,0.0004419679,0.6147279,0.01865409,0.2915006,0.003126371,0.06527703],"study_design_scores_gemma":[0.00001321833,0.00005468416,0.000503125,0.0000152658,0.00001545055,0.0001014766,0.0000314946,0.865464,0.001697644,0.1313381,0.0007547148,0.00001078002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1544321,0.0006678614,0.8373845,0.0008431157,0.00009066302,0.0000500253,0.0001745142,0.0004099894,0.005947244],"genre_scores_gemma":[0.9362187,0.0004127096,0.0598288,0.00020655,0.00006186156,0.00008451079,0.0001770406,0.00003890284,0.002971004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002289397,"threshold_uncertainty_score":0.007869959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1606850996455916,"score_gpt":0.3665795499682203,"score_spread":0.2058944503226287,"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."}}