{"id":"W3153478508","doi":"10.1523/eneuro.0076-21.2021","title":"Object and Spatial Context Representations in Visual Short-Term Memory","year":2021,"lang":"en","type":"letter","venue":"eNeuro","topic":"Memory and Neural Mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Term (time); Context (archaeology); Object (grammar); Computer science; Cognitive science; Visual short-term memory; Short-term memory; Cognitive psychology; Working memory; Psychology; Artificial intelligence; History; Cognition; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004868892,0.0004021456,0.0005954626,0.0004140133,0.0007590526,0.001918547,0.0007721981,0.004760375,0.006343095],"category_scores_gemma":[0.001327151,0.0003683417,0.000317615,0.0003615732,0.001429357,0.002127464,0.0007716549,0.003966776,0.003198023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008314942,"about_ca_system_score_gemma":0.0006468907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002714849,"about_ca_topic_score_gemma":0.007305599,"domain_scores_codex":[0.9998624,0.00001924874,0.00001323023,0.0000352433,0.00005176369,0.00001810499],"domain_scores_gemma":[0.9996002,0.0001950366,0.00003072688,0.0000210462,0.00009351471,0.00005937709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001314294,0.0000812958,0.0009499182,0.0005471486,0.00003702062,0.001913976,0.0001997611,0.0002866817,0.007914415,0.01940694,0.807238,0.1601105],"study_design_scores_gemma":[0.0005020955,0.0002966953,0.008279292,0.0006833217,0.00009573922,0.004291422,0.0003754807,0.00338775,0.007291296,0.1132091,0.8614761,0.000111881],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01167634,0.2997265,0.003898592,0.5304357,0.1005853,0.00004877536,0.0006718601,0.0003470138,0.05261005],"genre_scores_gemma":[0.125273,0.3016701,0.003676792,0.1759616,0.2109433,0.0002570827,0.0006053251,0.0001446142,0.1814681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006343095,"threshold_uncertainty_score":0.02121979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09258628920586823,"score_gpt":0.3394851641649718,"score_spread":0.2468988749591035,"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."}}