{"id":"W4387934011","doi":"10.32920/24438040","title":"Multielement Episodic Encoding in Young and Older Adults","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Memory Processes and Influences","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Psychology; Context (archaeology); Set (abstract data type); Encoding (memory); Episodic memory; Young adult; Developmental psychology; Object (grammar); Cognitive psychology; Associative property; Multivariate statistics; Cognition; Computer science; Neuroscience; Artificial intelligence; Machine learning; Biology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002723252,0.0002062165,0.0002318195,0.0001803941,0.00007486082,0.0001324219,0.000316005,0.0001299873,0.0002023814],"category_scores_gemma":[0.0004093544,0.0001734472,0.00003735177,0.0001701189,0.00006672731,0.0001242981,0.0007961241,0.0003796822,0.00006554852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002984034,"about_ca_system_score_gemma":0.00004650133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009355012,"about_ca_topic_score_gemma":0.0005876161,"domain_scores_codex":[0.9981626,0.00005197663,0.0003668326,0.0008463647,0.0002711329,0.0003010412],"domain_scores_gemma":[0.9993746,0.0001452069,0.0001191944,0.0002684083,0.00002169034,0.00007095224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004743119,0.001194144,0.62538,0.01970121,0.00006464255,0.001184629,0.06070342,0.006115945,0.1175966,0.01582602,0.005980446,0.1457787],"study_design_scores_gemma":[0.005828925,0.000345506,0.3760644,0.009898672,0.00006396545,0.00008188363,0.0100491,0.1150577,0.4592867,0.01744093,0.001694038,0.004188116],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904943,0.0001159418,0.0001103477,0.0003784104,0.0007906171,0.0005402445,0.00001176032,0.0001436788,0.007414749],"genre_scores_gemma":[0.9960961,0.001164748,0.0002319983,0.0003555642,0.00005661451,0.0001072105,0.000002743992,0.00001839485,0.001966614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3416902,"threshold_uncertainty_score":0.707297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05944708885950337,"score_gpt":0.3132643797801763,"score_spread":0.253817290920673,"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."}}