{"id":"W2964812680","doi":"10.1523/jneurosci.0584-19.2019","title":"Semantic Context Enhances the Early Auditory Encoding of Natural Speech","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":163,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"Science Foundation Ireland","keywords":"Computer science; Neurocomputational speech processing; Speech perception; Speech recognition; Context (archaeology); Perception; Semantic similarity; Speech processing; Speech production; Encoding (memory); Active listening; Cognitive psychology; Psychology; Natural language processing; Artificial intelligence; Communication","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":[0.0002278279,0.0002701645,0.0001466602,0.0001493856,0.0000903256,0.0004057534,0.000120318,0.0002334646,0.002865962],"category_scores_gemma":[0.001878306,0.0001579467,0.0001607808,0.00008210812,0.0003291866,0.0004444179,0.0004318233,0.0001901502,0.0002110856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008490928,"about_ca_system_score_gemma":0.0001470994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002375845,"about_ca_topic_score_gemma":0.0005218924,"domain_scores_codex":[0.9998962,0.00002382047,0.000008962064,0.00003741541,0.00002107143,0.00001256217],"domain_scores_gemma":[0.9994863,0.0003127446,0.00009002357,0.00003850045,0.00003662171,0.00003573341],"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":[0.0006932165,0.00003260977,0.003421095,0.0001850005,0.00001811518,0.0001309666,0.0002135162,0.0003345306,0.9748712,0.0004244975,0.00005771823,0.01961749],"study_design_scores_gemma":[0.00008003362,0.002338639,0.5958882,0.00004842526,0.0001272952,0.001257502,0.0004914708,0.0125573,0.3815592,0.003956745,0.001652988,0.00004217601],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899372,0.0002045056,0.008066111,0.00007732375,0.0000234024,0.00001626295,0.00007233588,0.00009230026,0.001510664],"genre_scores_gemma":[0.9956419,0.00008542228,0.003854599,0.00002273831,0.0000166879,0.000008486142,0.00005365729,0.00001721594,0.0002991933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002865962,"threshold_uncertainty_score":0.009587646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03339690351508097,"score_gpt":0.2866300790466094,"score_spread":0.2532331755315285,"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."}}