{"id":"W2616571613","doi":"10.1016/j.neuroimage.2017.05.030","title":"Electrophysiological signatures of phonological and semantic maintenance in sentence repetition","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Heart and Stroke Foundation; Baycrest Hospital","funders":"Alzheimer's Association","keywords":"Sentence; Repetition (rhetorical device); Psychology; Recall; Cognitive psychology; Semantic memory; Cognition; Computer science; Linguistics; Natural language processing; 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":[0.0004867769,0.0002747655,0.0002006369,0.000370045,0.0001742434,0.0005841656,0.0002914192,0.0006891181,0.003438615],"category_scores_gemma":[0.003267323,0.0002741845,0.0001984414,0.0002473666,0.0006139512,0.0008666464,0.0003743402,0.0006170319,0.0004681705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000141544,"about_ca_system_score_gemma":0.0002680166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00111318,"about_ca_topic_score_gemma":0.001730395,"domain_scores_codex":[0.9998479,0.00003259064,0.00001494418,0.00003709466,0.00003351198,0.00003401022],"domain_scores_gemma":[0.9989228,0.000556578,0.0002476822,0.00006658716,0.0001181675,0.00008823063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001808079,0.0001151125,0.01277307,0.0001128579,0.00005622213,0.0004745708,0.0004736797,0.0001660964,0.9621451,0.0009007499,0.0001929359,0.02078151],"study_design_scores_gemma":[0.0002150315,0.0008191639,0.8756059,0.00005162149,0.0001536545,0.00325311,0.0008109182,0.002516325,0.1121245,0.003714991,0.0006949091,0.00003978127],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944864,0.0002780856,0.002680479,0.0001452848,0.00002256537,0.00002878496,0.0002475997,0.00003014237,0.002080725],"genre_scores_gemma":[0.9973004,0.000126915,0.001222579,0.00006261717,0.00002496046,0.00004028873,0.0002156263,0.00002814807,0.000978439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003438615,"threshold_uncertainty_score":0.01150334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02840087892601153,"score_gpt":0.2879540985903737,"score_spread":0.2595532196643622,"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."}}