{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009506307,0.00006688257,0.00010918,0.00004140252,0.00004546493,0.00001061672,0.0002258159,0.00002143651,0.00006263022],"category_scores_gemma":[0.000204653,0.00004467677,0.00005025002,0.0002707196,0.0001674827,0.0001170705,0.00007160953,0.0001296942,0.000009594846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000092982,"about_ca_system_score_gemma":0.00007222495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003837771,"about_ca_topic_score_gemma":6.997287e-7,"domain_scores_codex":[0.9989685,0.00008258965,0.0001892383,0.0002149604,0.0004182134,0.0001265375],"domain_scores_gemma":[0.9996794,0.00007475306,0.00008933363,0.00008795362,0.00002978354,0.00003870234],"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":[0.00006986473,0.0001441066,0.0003616351,0.00001172757,3.853817e-7,0.000004029694,0.001646499,0.007324377,0.9824731,0.006570428,0.0009135652,0.0004802842],"study_design_scores_gemma":[0.0005341122,0.0003100922,0.009045404,0.00005348547,0.000005164627,0.0000111069,0.0002296442,0.8798356,0.1083396,0.001351833,0.0001967348,0.00008723282],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914537,0.000002733991,0.00431754,0.003589158,0.00006425561,0.0002337674,0.00003001498,0.00001234068,0.0002964763],"genre_scores_gemma":[0.9967992,0.000003229935,0.001616684,0.001501518,0.00003194234,0.00001196425,0.000003191814,0.000004190187,0.00002807404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8741335,"threshold_uncertainty_score":0.1821866,"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."}}