{"id":"W3115250497","doi":"10.14288/1.0395431","title":"AudioViewer : learning to visualize sound","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Perception; Speech recognition; Task (project management); Parsing; Human–computer interaction; Natural language processing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003854085,0.000766455,0.000193869,0.0002372072,0.000105807,0.0005353129,0.0008268747,0.0006263509,0.01024398],"category_scores_gemma":[0.002538975,0.00019155,0.0003961576,0.0001352392,0.0003477369,0.001154071,0.0009760602,0.0006019949,0.001991363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002168097,"about_ca_system_score_gemma":0.0002349548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000939518,"about_ca_topic_score_gemma":0.002443076,"domain_scores_codex":[0.9998744,0.00004239349,0.000003955254,0.00004138279,0.00002759108,0.00001032926],"domain_scores_gemma":[0.9995736,0.0002659248,0.00002597932,0.00005227667,0.00004043374,0.00004174312],"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":[0.0008725696,0.0002755619,0.002814369,0.000454898,0.00008868647,0.0004010891,0.0005018662,0.03934743,0.07410412,0.01114879,0.02699559,0.842995],"study_design_scores_gemma":[0.0001818789,0.001172953,0.005256035,0.0001930992,0.0001259518,0.001529316,0.0004334096,0.8029653,0.06970049,0.03970954,0.07862165,0.0001102153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.07120767,0.00118643,0.8974312,0.001096388,0.0002807055,0.0001775077,0.001495244,0.0148994,0.0122254],"genre_scores_gemma":[0.5351045,0.001551541,0.4443995,0.0005348697,0.0001065466,0.0003397163,0.001981507,0.0008671081,0.0151148],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01024398,"threshold_uncertainty_score":0.03426951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07185193581436541,"score_gpt":0.2138351985592266,"score_spread":0.1419832627448612,"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."}}