{"id":"W2750318064","doi":"10.1101/181354","title":"Slot-like capacity and resource-like coding in a neural model of multiple-item working memory","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Working memory; Coding (social sciences); Computer science; Fidelity; Artificial neural network; Short-term memory; Function (biology); Artificial intelligence; Cognition; Neuroscience; Psychology; Mathematics; Biology","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":[0.0006778687,0.0002630191,0.0006177365,0.0003876272,0.0003881412,0.001143128,0.001694023,0.001187973,0.002552009],"category_scores_gemma":[0.002397921,0.0003579081,0.0007745709,0.0003822438,0.001298426,0.002066775,0.0007081996,0.0008290922,0.0002391331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001307605,"about_ca_system_score_gemma":0.000693773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005859352,"about_ca_topic_score_gemma":0.003221717,"domain_scores_codex":[0.9998388,0.00004947923,0.000007977077,0.00003692294,0.00002802367,0.00003870879],"domain_scores_gemma":[0.9991661,0.000463587,0.0001021767,0.00009583004,0.0000818105,0.00009045764],"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":[0.0001116742,0.00005239419,0.001084114,0.00004586581,0.00003184293,0.0001366855,0.0001269348,0.9415418,0.008916713,0.04486518,0.0003861848,0.002700625],"study_design_scores_gemma":[0.0000116606,0.00001282137,0.000240822,0.00000247833,0.000003792223,0.00001556943,0.000008184174,0.9884714,0.000294047,0.0108627,0.00007071693,0.000005728937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7690674,0.0003295969,0.2182175,0.001782396,0.00007621695,0.00004477467,0.0003124752,0.0002227151,0.009947001],"genre_scores_gemma":[0.9914322,0.00009840553,0.006514324,0.00005987428,0.00001137897,0.00004663983,0.00003251597,0.00001953106,0.001785198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005859352,"threshold_uncertainty_score":0.0116505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05530301555156959,"score_gpt":0.2336747867756786,"score_spread":0.178371771224109,"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."}}