{"id":"W3016014060","doi":"10.3390/app10072468","title":"Automatic Staff Reconstruction within SIMSSA Project","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Music and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Universidad de Málaga; McGill University","keywords":"Musical; Computer science; Identification (biology); Scheme (mathematics); Task (project management); Object (grammar); Process (computing); Artificial intelligence; Engineering; Visual arts; Art; Mathematics; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.000378057,0.0000995721,0.0001215426,0.00006076973,0.0003766966,0.0003927145,0.0007977224,0.00003010083,0.00002689172],"category_scores_gemma":[0.00003525737,0.00007732421,0.00002272241,0.001126265,0.0002442711,0.0005623006,0.0001413407,0.00009155927,0.00006526336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001232501,"about_ca_system_score_gemma":0.0002665646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005502745,"about_ca_topic_score_gemma":0.000001687799,"domain_scores_codex":[0.9987574,0.00002077356,0.0001981946,0.0004523918,0.0003499221,0.0002213609],"domain_scores_gemma":[0.9995893,0.0000403778,0.0001355565,0.0001424094,0.00002041286,0.00007190502],"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":[0.000002668583,0.00002964383,0.0001684005,0.00006979695,0.000008382671,0.000004555226,0.01143396,0.0004552564,0.01182218,0.1263206,0.003367422,0.8463171],"study_design_scores_gemma":[0.0003337235,0.0002042896,0.0001215918,0.00005644717,0.000007635271,0.00003818437,0.002461484,0.9453351,0.02975911,0.01874811,0.002461909,0.0004724209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4764319,0.00007252112,0.433178,0.007378255,0.0006139479,0.0004438081,9.282294e-7,0.0009831781,0.08089747],"genre_scores_gemma":[0.8628637,0.000001223787,0.1355279,0.001497083,0.00007684305,0.00001236027,1.917395e-7,0.00000283282,0.00001789475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9448798,"threshold_uncertainty_score":0.3786955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04477616431578248,"score_gpt":0.2610111781570528,"score_spread":0.2162350138412703,"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."}}