{"id":"W2123405370","doi":"10.1162/jocn_a_00758","title":"The Impact of Musicianship on the Cortical Mechanisms Related to Separating Speech from Background Noise","year":2014,"lang":"en","type":"article","venue":"Journal of Cognitive Neuroscience","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal; International Laboratory for Brain, Music and Sound Research; Centre for Research on Brain Language and Music","funders":"","keywords":"N400; Psychology; Active listening; Noise (video); Audiology; Task (project management); Background noise; Speech recognition; Reading (process); Speech perception; Communication; Cognitive psychology; Perception; Event-related potential; Electroencephalography; Acoustics; Linguistics; Computer science; Neuroscience; Artificial intelligence","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":[0.0001650492,0.0003509041,0.0001574313,0.0002257986,0.000142985,0.0002548791,0.0001491648,0.0003253803,0.002684655],"category_scores_gemma":[0.001255351,0.0001022583,0.0001640906,0.00008448106,0.0003310649,0.0002508512,0.0003744026,0.0002372371,0.00023976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009585018,"about_ca_system_score_gemma":0.0001168632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003557361,"about_ca_topic_score_gemma":0.0006188261,"domain_scores_codex":[0.9998399,0.00003769656,0.00001229403,0.00004182709,0.00003865666,0.00002969599],"domain_scores_gemma":[0.999493,0.000204784,0.00009098177,0.00004387022,0.0000497172,0.0001176533],"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":[0.001979034,0.0001311197,0.006460735,0.00008467292,0.00002904324,0.0002736673,0.0002196254,0.0000626372,0.9664891,0.00008498138,0.00005695866,0.02412852],"study_design_scores_gemma":[0.0001217959,0.003240638,0.8761503,0.0000234428,0.0001016226,0.0008633736,0.0005656378,0.0004798364,0.1169712,0.0005074036,0.0009581022,0.00001670893],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979541,0.0003657764,0.0003891143,0.00005448981,0.00001306285,0.00000661984,0.00002213011,0.000008578319,0.00118612],"genre_scores_gemma":[0.998439,0.0002246586,0.0005104608,0.00006610269,0.00002079111,0.00001047883,0.00003308662,0.000006063838,0.0006893099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002684655,"threshold_uncertainty_score":0.008981049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06260708751514106,"score_gpt":0.3532346190160601,"score_spread":0.290627531500919,"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."}}