{"id":"W1554696566","doi":"","title":"Does a continuous masker makes speech comprehension in noise effortful","year":2004,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Speech recognition; Noise (video); Speech perception; Word (group theory); Perception; Masking (illustration); Comprehension; Character (mathematics); Interval (graph theory); Psychology; Computer science; Linguistics; Mathematics; Artificial intelligence; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001359839,0.0002533597,0.0003495799,0.0002175262,0.0001902888,0.0008184482,0.0002620281,0.001166558,0.003747298],"category_scores_gemma":[0.01701125,0.0002715204,0.0001792881,0.00007390358,0.0006874242,0.001057806,0.0004213003,0.0004407609,0.0008971402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001777311,"about_ca_system_score_gemma":0.0002810224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000747495,"about_ca_topic_score_gemma":0.0007702535,"domain_scores_codex":[0.9992641,0.0002146428,0.00007048866,0.0001365794,0.0002241587,0.00009005737],"domain_scores_gemma":[0.9915738,0.005298479,0.001356704,0.0005265903,0.0006265049,0.000617874],"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":[0.006010657,0.001004978,0.05688635,0.0003939311,0.0001508827,0.0009831915,0.005008883,0.0003742559,0.8646111,0.000809509,0.001203387,0.06256296],"study_design_scores_gemma":[0.0002624647,0.007130103,0.837227,0.0001071405,0.0003160173,0.003260496,0.004746759,0.004029998,0.1341262,0.002826904,0.005860609,0.0001063545],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966534,0.0001357768,0.0009972745,0.0002718854,0.00005174406,0.00001711926,0.00002040677,0.00003813643,0.001814187],"genre_scores_gemma":[0.9982552,0.00009057017,0.0006952285,0.00009811144,0.00002891946,0.00001835413,0.00003128169,0.00003470197,0.0007476392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003747298,"threshold_uncertainty_score":0.01253593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0152750583761146,"score_gpt":0.2420763627791734,"score_spread":0.2268013044030588,"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."}}