{"id":"W4206864959","doi":"","title":"Proceedings of the International Conference on Technologies for Music Notation and Representation – TENOR'18","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Notation; Representation (politics); Linguistics; Computer science; Cognitive science; Psychology; Political science; Philosophy; Law","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":[0.003674024,0.001281681,0.001526385,0.001296135,0.0009512048,0.005112136,0.001500611,0.001286206,0.09012973],"category_scores_gemma":[0.003546074,0.000398021,0.0009767392,0.001472945,0.001005164,0.00354319,0.002734942,0.00229477,0.04039005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001056728,"about_ca_system_score_gemma":0.002218692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004720556,"about_ca_topic_score_gemma":0.005842458,"domain_scores_codex":[0.9983832,0.0003994678,0.0001159128,0.0002804214,0.0006049383,0.0002160993],"domain_scores_gemma":[0.9973687,0.0003916221,0.00005108558,0.0005372106,0.001207376,0.0004439435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006789753,0.0003970714,0.0009159687,0.0004940305,0.00006885618,0.0002358604,0.0006532731,0.0009268569,0.0172581,0.03884765,0.39658,0.5429434],"study_design_scores_gemma":[0.00003283301,0.0001520153,0.001234432,0.0002172593,0.00004222151,0.0002870392,0.0003309753,0.004401076,0.006507537,0.01011676,0.9766484,0.00002940613],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02593672,0.0366762,0.4879434,0.01371621,0.05729755,0.0009239998,0.004119988,0.01302286,0.360363],"genre_scores_gemma":[0.05731507,0.01870842,0.14917,0.001485995,0.003668701,0.0004593236,0.01075201,0.004096585,0.7543439],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.09012973,"threshold_uncertainty_score":0.301514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0459374820036097,"score_gpt":0.2686859268256247,"score_spread":0.222748444822015,"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."}}