{"id":"W2111264611","doi":"10.1016/j.heares.2004.03.010","title":"The effect of perceived spatial separation on informational masking of Chinese speech","year":2004,"lang":"en","type":"article","venue":"Hearing Research","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Loudspeaker; Masking (illustration); Nonsense; Speech recognition; Noise (video); Speech perception; Psychology; Separation (statistics); Audiology; Acoustics; Computer science; Perception; Mathematics; Physics; Artificial intelligence; Statistics; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001968394,0.00006547225,0.0001099177,0.0001588094,0.0003451692,0.000043711,0.0001630235,0.00004796929,0.00001025986],"category_scores_gemma":[0.003753316,0.00003920176,0.00005172952,0.0003613092,0.0002386419,0.0001230557,0.00006796047,0.000287501,0.00003559082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008435112,"about_ca_system_score_gemma":0.00008876342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004043818,"about_ca_topic_score_gemma":0.00001402284,"domain_scores_codex":[0.9981802,0.0002987011,0.0002532406,0.0001424045,0.0009015253,0.0002239753],"domain_scores_gemma":[0.9973388,0.002245307,0.0000525836,0.0002137648,0.0001099712,0.00003952402],"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":[0.0003420128,0.0000513864,0.01673846,0.0001840802,0.000003358183,0.000001971897,0.002261252,0.01126317,0.9506755,0.002593796,0.000008457035,0.0158765],"study_design_scores_gemma":[0.0006132771,0.001059135,0.7290799,0.0001138238,9.118876e-7,0.000004801715,0.0000361151,0.00403846,0.263456,0.001505151,0.00004234027,0.00005009197],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996737,0.00000458497,0.0000841228,0.0002954739,0.00008451918,0.000349251,0.000001747774,0.00001315783,0.002430112],"genre_scores_gemma":[0.999774,0.000008463202,0.00006494042,0.000007135049,0.00005135519,0.00001666433,0.000001236247,0.000006793334,0.00006940949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7123415,"threshold_uncertainty_score":0.4493341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05602946810909389,"score_gpt":0.4168822790562442,"score_spread":0.3608528109471503,"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."}}