{"id":"W7019364055","doi":"","title":"Graphical Performance Software in Contexts: Explorations with Different Strokes","year":2012,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Software; Interface (matter); Graphical user interface; Context (archaeology); Adaptation (eye); Situated; User interface; Graphical user interface testing","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":[0.002492412,0.0009771883,0.0007019884,0.002134165,0.00204075,0.007354186,0.00135899,0.001327236,0.00474264],"category_scores_gemma":[0.01182865,0.0007634403,0.001076369,0.001485349,0.005179912,0.009290247,0.006827123,0.002040408,0.0004987445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008141979,"about_ca_system_score_gemma":0.0005809413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009969999,"about_ca_topic_score_gemma":0.001826086,"domain_scores_codex":[0.9955414,0.002708302,0.0001890629,0.0004812246,0.00078475,0.0002952888],"domain_scores_gemma":[0.9937383,0.005104325,0.0002162136,0.0005487333,0.0001910208,0.0002014794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005220726,0.0002759051,0.01696455,0.001445501,0.0001192789,0.003856836,0.4476322,0.006347355,0.04367431,0.1619816,0.002799448,0.3143811],"study_design_scores_gemma":[0.0001718365,0.001639224,0.03958358,0.002282989,0.0003236109,0.00889294,0.324749,0.05394418,0.03118755,0.2563269,0.2804018,0.0004964116],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.708859,0.001898466,0.2409235,0.001512838,0.00007749394,0.0001589413,0.0001168956,0.001028143,0.04542475],"genre_scores_gemma":[0.9093986,0.0007501084,0.0856614,0.0001768161,0.00002587281,0.0001107734,0.00009083305,0.0004396278,0.00334604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007354186,"threshold_uncertainty_score":0.01586574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983623003055273,"score_gpt":0.2196073609878539,"score_spread":0.1997711309573012,"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."}}