{"id":"W3209514945","doi":"10.5281/zenodo.2558826","title":"Predictive Musical Interaction with MDRNNs","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Norges Forskningsråd","keywords":"Musical; Computer science; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002736308,0.00009115796,0.00007919539,0.0001214101,0.001612987,0.0009449752,0.0009267037,0.00003189797,0.002322756],"category_scores_gemma":[0.0001358062,0.00007935609,0.00001974163,0.0005199201,0.0001889157,0.00072369,0.0008395332,0.0001740937,0.003547586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000074966,"about_ca_system_score_gemma":0.000004951021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004557204,"about_ca_topic_score_gemma":2.30339e-7,"domain_scores_codex":[0.9988605,0.0001177843,0.0001207524,0.0003741057,0.0002847507,0.0002421194],"domain_scores_gemma":[0.9989274,0.00001347647,0.00007506961,0.0003555916,0.0005143097,0.0001142274],"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":[0.0001490557,0.000217389,0.000006380162,0.00004063781,0.00005788565,0.0000279056,0.008710541,0.00005198392,0.005043105,0.02270921,0.2748077,0.6881782],"study_design_scores_gemma":[0.000306153,0.0006101318,0.000506478,0.00004474476,0.000005573004,0.0001749227,0.0001616681,0.01045951,0.001590127,0.0003425852,0.9856615,0.0001366032],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01491168,0.000008640952,0.7840693,0.00137225,0.0001564881,0.0001625152,0.000009247041,0.0009827655,0.1983271],"genre_scores_gemma":[0.9948376,0.000004111417,0.003558247,0.0004855378,0.0003405233,2.113119e-8,0.00005711209,0.0003153778,0.000401459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9799259,"threshold_uncertainty_score":0.9996868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03118233145871513,"score_gpt":0.2481070852713115,"score_spread":0.2169247538125964,"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."}}