{"id":"W2109781405","doi":"","title":"THE EFFECT OF MASKER TYPE AND WORD POSITION ON IMMEDIATE SENTENCE RECALL","year":2008,"lang":"en","type":"article","venue":"Proceedings of Fechner Day","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Masking (illustration); Noise (video); Speech recognition; Nonsense; Sentence; Word (group theory); Computer science; QUIET; Acoustics; Mathematics; Artificial intelligence; Physics","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":[0.0004019621,0.00007317915,0.0001098463,0.0000474066,0.0001274367,0.00001221411,0.00009759884,0.00004471357,0.000001517067],"category_scores_gemma":[0.001231779,0.00004325124,0.00002542041,0.000235751,0.0002359819,0.0001023413,0.00003544708,0.0001025176,0.000004434036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001175904,"about_ca_system_score_gemma":0.000008014763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007568308,"about_ca_topic_score_gemma":7.522937e-8,"domain_scores_codex":[0.9993435,0.00001819935,0.0001492829,0.0001695432,0.0001994304,0.000120053],"domain_scores_gemma":[0.9992652,0.0004553474,0.00009570563,0.00005760897,0.00009352605,0.00003264161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001101669,0.00002023052,0.01074117,0.0000732447,0.000001765732,6.460431e-7,0.0003518047,8.689197e-7,0.9822083,0.0006912374,0.0001968806,0.005603661],"study_design_scores_gemma":[0.0002438826,0.00102887,0.1301379,0.0001069083,0.000006957015,0.00001437437,0.00002743153,0.0001231991,0.8676822,0.0003240427,0.0002389642,0.00006523979],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997798,0.00002893908,0.000002224311,0.0005138241,0.0001018704,0.0001973882,0.000001211835,0.00002146803,0.001335096],"genre_scores_gemma":[0.9995062,0.0001684816,0.000072478,0.00003986541,0.00002307029,0.000009061027,2.167532e-7,0.000007412828,0.0001732004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1193968,"threshold_uncertainty_score":0.1763734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01543962150850673,"score_gpt":0.2505007808901206,"score_spread":0.2350611593816138,"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."}}