{"id":"W2156926590","doi":"10.1016/j.heares.2004.10.007","title":"Attribute capture in the precedence effect for long-duration noise sounds","year":2004,"lang":"en","type":"article","venue":"Hearing Research","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lagging; Precedence effect; Acoustics; Perception; Sound (geography); Noise (video); Reflection (computer programming); Fuse (electrical); Audiology; Computer science; Psychology; Physics; Mathematics; Artificial intelligence; Image (mathematics); Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004011987,0.0005058455,0.0008282295,0.0008903926,0.0008539472,0.003696854,0.00107035,0.001835414,0.01065671],"category_scores_gemma":[0.04331327,0.00128554,0.0005749508,0.0006099848,0.001072505,0.004474393,0.0025531,0.002131247,0.001036124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005015841,"about_ca_system_score_gemma":0.0008657009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002947819,"about_ca_topic_score_gemma":0.003086798,"domain_scores_codex":[0.9983878,0.0002792082,0.00008958292,0.0004738914,0.0005910286,0.0001784838],"domain_scores_gemma":[0.9785614,0.01553324,0.001315379,0.002389092,0.0009411494,0.001259738],"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":[0.008549215,0.001052265,0.06997172,0.0006842148,0.0004155018,0.001201365,0.00385927,0.008040503,0.7254422,0.04991188,0.002014511,0.1288573],"study_design_scores_gemma":[0.0005632738,0.001119381,0.8090259,0.0001760565,0.0006395421,0.003822803,0.001111846,0.04385985,0.03575739,0.09923725,0.004402651,0.0002841116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9459968,0.0006243102,0.02165348,0.0003531193,0.0002246276,0.00005069991,0.0001798747,0.000192243,0.03072473],"genre_scores_gemma":[0.9933564,0.000163438,0.003596808,0.0002280534,0.00009353761,0.00001895476,0.0001948101,0.000210773,0.00213721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01065671,"threshold_uncertainty_score":0.03565025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1594744255915971,"score_gpt":0.4338142153953534,"score_spread":0.2743397898037563,"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."}}