{"id":"W2010567361","doi":"10.1177/1541931213571256","title":"Music as an Auditory Display","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Auditory display; Musical; Mode (computer interface); Psychology; Auditory scene analysis; Human–computer interaction; Perception; Multimedia; Speech recognition; Cognitive psychology","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":[0.001016731,0.0004753099,0.000281717,0.0004778131,0.0003982643,0.002080146,0.0007617089,0.0006824398,0.01081479],"category_scores_gemma":[0.003967701,0.0001995411,0.000289797,0.0003189368,0.0005597381,0.001342686,0.001371004,0.0003392101,0.001606133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001609934,"about_ca_system_score_gemma":0.0002091017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001883941,"about_ca_topic_score_gemma":0.0002321638,"domain_scores_codex":[0.9990534,0.0003341981,0.00005724554,0.00008314494,0.0004085514,0.00006349666],"domain_scores_gemma":[0.9985009,0.000696716,0.0001219286,0.0001773167,0.0003322992,0.0001708674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002200637,0.0002204367,0.003730763,0.001753394,0.0001057204,0.0006707118,0.001342076,0.002247513,0.6229431,0.009217571,0.004214039,0.351354],"study_design_scores_gemma":[0.001116455,0.01919263,0.06153669,0.001533467,0.001373604,0.01292888,0.002876026,0.03011264,0.4261367,0.02116898,0.4214996,0.0005243712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5931076,0.01278248,0.2705806,0.002202864,0.002096426,0.0008318336,0.0007147886,0.003818988,0.1138644],"genre_scores_gemma":[0.8836474,0.003065595,0.09741019,0.0006872521,0.0003834375,0.0001779107,0.0001745929,0.0002029358,0.01425073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01081479,"threshold_uncertainty_score":0.03617907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01999873005382169,"score_gpt":0.2874222099557824,"score_spread":0.2674234799019607,"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."}}