{"id":"W2919875924","doi":"10.1145/3308557.3308686","title":"Relaxation \"sweet spot\" exploration in pantophonic musical soundscape using reinforcement learning","year":2019,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Soundscape; Reinforcement learning; Avatar; Relaxation (psychology); Musical; Speech recognition; Active listening; Acoustics; Polyphony; Human–computer interaction; Artificial intelligence; Sound (geography); Psychology; Communication; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003510558,0.0005260677,0.0004580308,0.00024748,0.0002038592,0.0003796874,0.0004645364,0.0003862132,0.001596973],"category_scores_gemma":[0.001033315,0.0002368562,0.0003340941,0.000138408,0.0003947752,0.0004475437,0.0007114662,0.0003475171,0.0001601083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001872106,"about_ca_system_score_gemma":0.0002651962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000999208,"about_ca_topic_score_gemma":0.001568375,"domain_scores_codex":[0.9998375,0.00004823559,0.000006200803,0.00005941379,0.00002219763,0.00002643994],"domain_scores_gemma":[0.9997154,0.0001545857,0.00003670252,0.00002121359,0.00003160791,0.00004051768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001453738,0.0008488866,0.01183838,0.0004536408,0.000230601,0.0006739818,0.0007739855,0.3354297,0.1593376,0.004327578,0.002113914,0.482518],"study_design_scores_gemma":[0.00003935064,0.0003148166,0.003123368,0.0000125841,0.00002948286,0.0001044991,0.00008209977,0.985344,0.007580189,0.002699518,0.0006492617,0.00002071986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3701193,0.0003935367,0.6241594,0.0001690455,0.0000476218,0.0001119032,0.00005916132,0.001205699,0.003734387],"genre_scores_gemma":[0.9278825,0.00007955968,0.07037501,0.00005079553,0.00001077294,0.00006744316,0.00004372543,0.00003254919,0.001457768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001596973,"threshold_uncertainty_score":0.005342484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06659803873143134,"score_gpt":0.2932553131839046,"score_spread":0.2266572744524733,"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."}}