{"id":"W3112049600","doi":"10.1101/2020.12.14.422659","title":"Multiple Temporal and Semantic Processes During Verbal Fluency Tasks in English-Russian Bilinguals","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging","keywords":"Verbal fluency test; Cognition; Recall; Task (project management); Psychology; Fluency; Cognitive psychology; Cluster (spacecraft); Demographics; Natural language processing; Computer science; Neuropsychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006771023,0.0005331466,0.0004545249,0.0005868398,0.000435554,0.0006290076,0.0001675086,0.0003916945,0.001715804],"category_scores_gemma":[0.00229892,0.0002055487,0.0002193165,0.0002167585,0.0004020373,0.0003137669,0.0003697397,0.0002736444,0.0004451889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000280277,"about_ca_system_score_gemma":0.0002583156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008391079,"about_ca_topic_score_gemma":0.009150584,"domain_scores_codex":[0.9996885,0.00008143414,0.00003852605,0.00008178195,0.0000570555,0.00005273788],"domain_scores_gemma":[0.9993493,0.0002181352,0.0002010736,0.00004867685,0.0001012682,0.00008155998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005141484,0.001150135,0.8788224,0.0001587461,0.0001674815,0.003966179,0.02036629,0.000400071,0.06728356,0.0003434737,0.0003285634,0.02187163],"study_design_scores_gemma":[0.0000455576,0.0009282044,0.9902011,0.00001433589,0.00003950853,0.002152697,0.003674644,0.0005312975,0.001943163,0.0001364425,0.0003141766,0.00001891404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997054,0.00002154452,0.00002548758,0.000004626823,0.000001330218,0.000002050223,0.00002819897,0.000001431745,0.0002099425],"genre_scores_gemma":[0.9996144,0.00001902285,0.00004875411,0.000006629639,0.000001683907,0.000003808138,0.00005245639,0.000002152378,0.000251175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008391079,"threshold_uncertainty_score":0.01668447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203193451182389,"score_gpt":0.2398673073640424,"score_spread":0.2195479622458035,"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."}}