{"id":"W2944083376","doi":"10.3390/vision3020021","title":"Eye Movements Actively Reinstate Spatiotemporal Mnemonic Content","year":2019,"lang":"en","type":"review","venue":"Vision","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mnemonic; Eye movement; Encoding (memory); Gaze; Context (archaeology); Psychology; Cognition; Cognitive psychology; Task (project management); Eye tracking; Computer science; Neuroscience; Artificial intelligence; Geography","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":[0.0005495847,0.001076195,0.001289877,0.002814843,0.0002259295,0.001037093,0.000903158,0.001233519,0.002719448],"category_scores_gemma":[0.001106242,0.0002655711,0.0005808001,0.001739347,0.000534472,0.001325516,0.0006861616,0.001046222,0.001876109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006921653,"about_ca_system_score_gemma":0.0007839055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001357791,"about_ca_topic_score_gemma":0.001854276,"domain_scores_codex":[0.9998634,0.00001789605,0.00002698412,0.00004200036,0.00003678351,0.00001292263],"domain_scores_gemma":[0.9995261,0.0002580041,0.00008064758,0.00001559389,0.00009388066,0.00002573903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007247434,0.00003774736,0.0002649558,0.01750005,0.0001120479,0.00008703268,0.00004460329,0.0002416067,0.002707071,0.00261999,0.008293783,0.9680187],"study_design_scores_gemma":[0.00003190287,0.0002592507,0.003901952,0.00756841,0.000369531,0.001860294,0.00009124888,0.000246189,0.003195453,0.004452178,0.9779686,0.00005488769],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001583279,0.9987893,0.0001651566,0.0001109065,0.00007424055,0.000003944982,0.00002071114,0.000008194166,0.0006693254],"genre_scores_gemma":[0.00143898,0.9976175,0.0001934269,0.00009577921,0.00009349448,0.000009418873,0.00004617079,0.000002394353,0.0005026814],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002814843,"threshold_uncertainty_score":0.009097517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1615045988620706,"score_gpt":0.4045380129736686,"score_spread":0.243033414111598,"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."}}