{"id":"W2767226973","doi":"","title":"Tuning to Trust: System Calibration as Creative Enabler","year":2017,"lang":"en","type":"article","venue":"University of Huddersfield Repository (University of Huddersfield)","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canada Council for the Arts; Centre for Interdisciplinary Research in Music Media and Technology","keywords":"Enabling; Software portability; Adaptability; Computer science; Set (abstract data type); Calibration; Field (mathematics); Quality (philosophy); Human–computer interaction; Multimedia; Psychology; Management","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01805405,0.001272905,0.0008167318,0.001089913,0.001491115,0.006042365,0.003153719,0.002320816,0.005833683],"category_scores_gemma":[0.07749349,0.0009761978,0.0007539467,0.000483113,0.003854292,0.01003662,0.01033769,0.003584997,0.001838759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377137,"about_ca_system_score_gemma":0.00221896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006798209,"about_ca_topic_score_gemma":0.0003806397,"domain_scores_codex":[0.9751243,0.01157312,0.001530042,0.003333705,0.006496074,0.001942834],"domain_scores_gemma":[0.9499596,0.02363047,0.004189028,0.01459007,0.006015732,0.001615075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001555551,0.0007303893,0.01236068,0.001569459,0.0002583997,0.001320136,0.01901878,0.05038,0.09684329,0.1617357,0.005974408,0.6482532],"study_design_scores_gemma":[0.000404187,0.003403082,0.006920801,0.001294987,0.0005257479,0.003212241,0.006362712,0.4156818,0.2371069,0.2131106,0.1113402,0.0006366752],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06194817,0.0003867649,0.916396,0.001193122,0.000146199,0.0006282414,0.0000317661,0.004490445,0.01477938],"genre_scores_gemma":[0.8434612,0.0001794128,0.1507176,0.0003496259,0.00007241319,0.0003825311,0.00006086786,0.0006985923,0.004077751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01805405,"threshold_uncertainty_score":0.09548008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181074717197522,"score_gpt":0.1862216435375048,"score_spread":0.1744108963655296,"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."}}