{"id":"W3104790520","doi":"10.3390/e22111291","title":"A Computational Model of Tonal Tension Profile of Chord Progressions in the Tonal Interval Space","year":2020,"lang":"en","type":"article","venue":"Entropy","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Centre for Interdisciplinary Research in Music Media and Technology","funders":"Erasmus+; European Commission","keywords":"Chord (peer-to-peer); Timbre; Melody; Musical; Cognitive dissonance; Tension (geology); Perception; Consonance and dissonance; Computer science; Speech recognition; Pitch (Music); Musical acoustics; Mathematics; Acoustics; Psychology; Compression (physics); Art; Social psychology; 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":[0.0002519233,0.0003227065,0.0003636761,0.0003714336,0.0003331063,0.0008326902,0.0007826631,0.0006546533,0.00277205],"category_scores_gemma":[0.00104883,0.0002075761,0.0004946959,0.0003353829,0.0004451677,0.0007984997,0.0005715695,0.0005507218,0.0002145546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004300481,"about_ca_system_score_gemma":0.0004540944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005753075,"about_ca_topic_score_gemma":0.003255182,"domain_scores_codex":[0.9999231,0.00002115972,0.000004011243,0.00002208663,0.00001745624,0.00001213431],"domain_scores_gemma":[0.9997899,0.0001217075,0.00002629671,0.0000146043,0.00002439723,0.0000229894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005782849,0.00002894717,0.0009542201,0.00003747503,0.00001762159,0.00009012362,0.00009451903,0.9682567,0.002760535,0.01856088,0.0002657141,0.008875393],"study_design_scores_gemma":[0.000002276505,0.000006013347,0.0001191133,0.000001583266,0.000001893715,0.000008249843,0.000004089526,0.9978272,0.00006058398,0.001900703,0.00006638725,0.000001910208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2427469,0.0004833845,0.7445524,0.0003871622,0.00004876318,0.00005711621,0.0002579142,0.0002395661,0.01122672],"genre_scores_gemma":[0.9647243,0.0002106651,0.03184816,0.00003698361,0.00002101779,0.00009224144,0.0001143567,0.00002966894,0.002922545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005753075,"threshold_uncertainty_score":0.01143914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07250946176048804,"score_gpt":0.3127792587561896,"score_spread":0.2402697969957016,"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."}}