{"id":"W2801493286","doi":"10.1080/14992027.2018.1441557","title":"Speech mapping and probe microphone measurements","year":2018,"lang":"en","type":"article","venue":"International Journal of Audiology","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Microphone; Audiology; Acoustics; Speech recognition; Medicine; Computer science; Physics; Loudspeaker","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":[0.0004717471,0.000994052,0.0005033346,0.0008498876,0.0003722716,0.0008913378,0.0005902874,0.001615158,0.007169699],"category_scores_gemma":[0.002446008,0.0003902856,0.0004024102,0.0007839996,0.0002879858,0.00126355,0.0009718474,0.0007421644,0.003877842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002393564,"about_ca_system_score_gemma":0.0003158393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001590969,"about_ca_topic_score_gemma":0.002148162,"domain_scores_codex":[0.9990065,0.0002039573,0.00003685514,0.0002132421,0.0004622035,0.00007738119],"domain_scores_gemma":[0.9993244,0.0002089085,0.00004018788,0.00006388018,0.000327261,0.00003535171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001545755,0.00008179434,0.002679361,0.0003634984,0.00005252771,0.0005437346,0.0004086902,0.002126767,0.8021798,0.001148282,0.005685067,0.1831848],"study_design_scores_gemma":[0.0001333944,0.001208789,0.05323803,0.0001015772,0.0001489318,0.006364167,0.0009206918,0.04572116,0.8484194,0.002102741,0.04144639,0.0001947108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.330579,0.004882412,0.6192164,0.00106575,0.002225597,0.0004808125,0.006836305,0.00625037,0.02846332],"genre_scores_gemma":[0.8070834,0.00164219,0.1682646,0.0004951552,0.0003637811,0.0003780824,0.002462688,0.000594171,0.01871602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007169699,"threshold_uncertainty_score":0.02398503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03511570995472064,"score_gpt":0.2868487463314626,"score_spread":0.2517330363767419,"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."}}