{"id":"W4234866094","doi":"10.31234/osf.io/e2unt","title":"Linking detail to temporal structure in naturalistic event recall","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Memory Processes and Influences","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Recall; Episodic memory; Contiguity; Context (archaeology); Cognitive psychology; Psychology; Context-dependent memory; Autobiographical memory; Recall test; Free recall; Event (particle physics); Encoding (memory); Serial position effect; Dynamics (music); Computer science; Cognition; History; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005624852,0.000172194,0.0001458177,0.0008729476,0.0001720138,0.0008451911,0.0001897008,0.0001756506,0.001118624],"category_scores_gemma":[0.006891446,0.0001771396,0.0001317287,0.0004619452,0.0005065413,0.0007711698,0.0008516589,0.0002267887,0.0001285093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002408828,"about_ca_system_score_gemma":0.0001613364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001462279,"about_ca_topic_score_gemma":0.002452336,"domain_scores_codex":[0.999754,0.00004246187,0.00002934157,0.00007496456,0.00008037072,0.00001892558],"domain_scores_gemma":[0.9978744,0.0006971036,0.0008094179,0.0003381465,0.0001748267,0.0001061636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003187883,0.0002186242,0.6317683,0.0005997583,0.0003669316,0.0006819086,0.01666564,0.002978983,0.1749029,0.003587299,0.0004248801,0.1646168],"study_design_scores_gemma":[0.00001654378,0.000349623,0.9763214,0.00004048115,0.00008237537,0.0008968905,0.001195226,0.001434006,0.01420104,0.004095384,0.001323999,0.00004310359],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963199,0.0003796366,0.002133167,0.00001249335,0.000002711684,0.00001066744,0.0001438129,0.00001282845,0.0009848],"genre_scores_gemma":[0.9977875,0.0001980182,0.001611988,0.000004588898,0.000004680709,0.000008068103,0.0001764958,0.000005903544,0.0002027666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001462279,"threshold_uncertainty_score":0.003742218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04826235605539689,"score_gpt":0.3189421103338499,"score_spread":0.270679754278453,"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."}}