{"id":"W2992584662","doi":"10.1145/3356590.3356624","title":"A study comparing shape, colour and texture as visual labels in audio sample browsers","year":2019,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Audio visual; Sample (material); Texture (cosmology); Task (project management); Artificial intelligence; Computer vision; Pattern recognition (psychology); Image (mathematics); Multimedia","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006177142,0.0008691185,0.00104295,0.001184186,0.0006717095,0.003345946,0.001320842,0.001517248,0.005623035],"category_scores_gemma":[0.1150228,0.0008559647,0.0007240198,0.0009198095,0.001035682,0.005861673,0.00137686,0.001588922,0.001225078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009011801,"about_ca_system_score_gemma":0.0007434248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005679026,"about_ca_topic_score_gemma":0.005291637,"domain_scores_codex":[0.9944133,0.002746077,0.0006250795,0.0008712942,0.001080212,0.0002640397],"domain_scores_gemma":[0.7711627,0.2040344,0.007950173,0.006213019,0.007795057,0.002844575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.05505634,0.03137561,0.326457,0.009440481,0.001216746,0.001314388,0.0402836,0.005798622,0.1802307,0.002518484,0.01045182,0.3358563],"study_design_scores_gemma":[0.005593613,0.06303237,0.7740469,0.001001628,0.002602536,0.001912149,0.01888046,0.05999779,0.05044445,0.002904823,0.01883642,0.0007468253],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949734,0.0003251682,0.00168594,0.000101198,0.00003266618,0.0003105452,0.0002514517,0.0001277776,0.002191907],"genre_scores_gemma":[0.9844152,0.0001960533,0.01146825,0.0003086178,0.00004683096,0.0005903342,0.0005524457,0.0001974333,0.002224874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006177142,"threshold_uncertainty_score":0.03266823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924191303408354,"score_gpt":0.2844963580344492,"score_spread":0.2652544450003657,"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."}}