{"id":"W2580747022","doi":"","title":"MALTA: Enhancing ACT-R with a Holographic Persistent Knowledge Store","year":2007,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cognitive architecture; Cognition; Cognitive science; Computer science; Content-addressable memory; Metamemory; Semantic memory; Recall; Cognitive model; Psychology; Cognitive psychology; Artificial intelligence; Metacognition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006014134,0.0003800802,0.0003189979,0.0003923601,0.0003232087,0.001761402,0.001094484,0.00015314,0.00004500759],"category_scores_gemma":[0.00008795192,0.0003046231,0.0002722904,0.001015246,0.0000856379,0.004365489,0.000416199,0.0006769461,0.001265406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007086823,"about_ca_system_score_gemma":0.0001356676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003184382,"about_ca_topic_score_gemma":0.00000489978,"domain_scores_codex":[0.9974065,0.00008191243,0.0004739455,0.0007404085,0.000449512,0.0008477559],"domain_scores_gemma":[0.9984963,0.0002102701,0.0001947961,0.000603751,0.00009584747,0.00039906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000374132,0.001082765,0.6485881,0.0004125017,0.0005642306,0.001308482,0.002250494,0.0001819815,0.002676087,0.2650186,0.00126032,0.07628231],"study_design_scores_gemma":[0.0007628502,0.0008528519,0.02375935,0.0006756518,0.00002634543,0.0002551298,0.0004530591,0.0003625771,0.008580297,0.00080882,0.9621793,0.001283735],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6773352,0.001160508,0.2471383,0.0003733934,0.0006749048,0.0005201867,0.00006889422,0.001535544,0.07119308],"genre_scores_gemma":[0.986394,0.000004549532,0.004858399,0.0002004641,0.0002729308,0.00001080375,0.00002578865,0.0000606447,0.008172437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.960919,"threshold_uncertainty_score":0.9999406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01511083324516034,"score_gpt":0.2178811335844339,"score_spread":0.2027703003392735,"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."}}