{"id":"W1999691406","doi":"10.1145/2750858.2804264","title":"SoQr","year":2015,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Xerox (Canada)","funders":"","keywords":"Computer science; Robustness (evolution); Microphone; Mel-frequency cepstrum; Impulse response; Speech recognition; Impulse (physics); Sine wave; Pattern recognition (psychology); Artificial intelligence; Feature extraction; Mathematics; Engineering; Telecommunications; Sound pressure; Voltage; Electrical engineering; Physics","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":[0.0008602672,0.0008111371,0.0005706729,0.0006571176,0.0005011697,0.001254337,0.001220004,0.0009471636,0.03660112],"category_scores_gemma":[0.003647354,0.0002985343,0.0005075979,0.0005690899,0.0004850793,0.002014175,0.001916615,0.0007387561,0.02410511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003006995,"about_ca_system_score_gemma":0.0005487441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001389779,"about_ca_topic_score_gemma":0.001323178,"domain_scores_codex":[0.998536,0.0001808228,0.00009536659,0.0003857057,0.0006689665,0.00013315],"domain_scores_gemma":[0.9984319,0.0002573603,0.0001027932,0.0004863808,0.0006548596,0.00006662708],"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":[0.0007729302,0.0001944921,0.004642622,0.0008583217,0.00007660808,0.0004719131,0.0007106849,0.00868528,0.08132525,0.03550116,0.1185367,0.7482241],"study_design_scores_gemma":[0.0001071854,0.0006932256,0.005441694,0.0001890066,0.00007482479,0.001637909,0.0006256411,0.1164284,0.06837554,0.02143607,0.7848275,0.0001630497],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04564234,0.001428365,0.7866279,0.001680805,0.001488662,0.0007078273,0.004929916,0.04807115,0.109423],"genre_scores_gemma":[0.4446106,0.001762719,0.3922187,0.003268381,0.0005160605,0.0006423683,0.01779461,0.005038184,0.1341484],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03660112,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06483271287492283,"score_gpt":0.2572287313650556,"score_spread":0.1923960184901328,"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."}}