{"id":"W4236460615","doi":"10.31234/osf.io/y4dpu","title":"Self-referential encoding of source information in recollection memory","year":2019,"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","funders":"","keywords":"Encoding (memory); Context-dependent memory; Recall; Computer science; Episodic memory; TRACE (psycholinguistics); Cognitive psychology; Memory errors; Context (archaeology); Explicit memory; Facilitation; Information source (mathematics); Psychology; Free recall; Cognition; Neuroscience","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":[0.0003164552,0.0001507647,0.0002458165,0.000357895,0.00004574907,0.00008770864,0.000330273,0.0002350521,0.0003214332],"category_scores_gemma":[0.0003834583,0.000134745,0.00006501061,0.0002659782,0.00002463303,0.0006277865,0.0003092314,0.0004219564,0.00008535257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006688198,"about_ca_system_score_gemma":0.000226537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002394997,"about_ca_topic_score_gemma":0.00003330514,"domain_scores_codex":[0.998605,0.00006787176,0.0005506751,0.0002835966,0.000329964,0.0001628928],"domain_scores_gemma":[0.9990754,0.0001236454,0.0004266881,0.0002712089,0.00007487239,0.00002821849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001082063,0.001323269,0.01155742,0.04055898,0.0001180066,0.000007882223,0.04830392,0.5420497,0.2087314,0.008634889,0.007414132,0.1302183],"study_design_scores_gemma":[0.0007508477,0.0001378321,0.0006999052,0.000429795,0.00002557197,0.000008432586,0.0009021194,0.0722835,0.915091,0.001821381,0.007307594,0.0005419646],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8305818,0.00001743943,0.002168734,0.00005001352,0.001387207,0.0005799662,0.000006421108,0.000112933,0.1650954],"genre_scores_gemma":[0.9974701,0.0002514401,0.0003690715,0.0001782022,0.00004764639,0.00002390494,0.000005968152,0.00000695304,0.001646672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7063596,"threshold_uncertainty_score":0.5494741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03670160744823021,"score_gpt":0.270549459963688,"score_spread":0.2338478525154578,"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."}}