{"id":"W2991077193","doi":"10.5281/zenodo.3527812","title":"Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony","year":2019,"lang":"en","type":"article","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; European Commission","keywords":"Rhythm; Harmony (color); Computer science; Syntax; Linguistics; Natural language processing; Artificial intelligence; Philosophy; Physics; Acoustics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001228317,0.0002730925,0.0004678979,0.000426698,0.00005982356,0.00006452225,0.0007333345,0.0003346305,0.001139784],"category_scores_gemma":[0.0001226629,0.000267325,0.000157185,0.0008162311,0.0002918646,0.0005321286,0.0001587575,0.0004382514,0.0005948168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001123471,"about_ca_system_score_gemma":0.0001569089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008762894,"about_ca_topic_score_gemma":0.00006509994,"domain_scores_codex":[0.9972894,0.0002036567,0.0006700466,0.0005719801,0.0004419315,0.000823027],"domain_scores_gemma":[0.9985233,0.000212157,0.0002607677,0.0007354352,0.00009382887,0.0001745446],"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":[0.0007915648,0.002399675,0.01747371,0.0004757079,0.0001314972,0.0003490564,0.01208529,0.0003382092,0.7579106,0.1185897,0.008552335,0.08090267],"study_design_scores_gemma":[0.005763021,0.002939507,0.0748209,0.001358352,0.0001920977,0.0007482699,0.003471358,0.0821635,0.6429609,0.1795616,0.002710377,0.003310116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9536154,0.0002546954,0.01249877,0.0003281538,0.0003121265,0.001192203,0.00004520655,0.0002451703,0.03150832],"genre_scores_gemma":[0.9899712,0.00003321036,0.004533307,0.0008556435,0.00005505961,0.0003024539,0.00001060278,0.0000337867,0.004204784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1149497,"threshold_uncertainty_score":0.9999779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0150791351758061,"score_gpt":0.2718166325603572,"score_spread":0.256737497384551,"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."}}