{"id":"W7052737325","doi":"","title":"Sex Classification Using In-ear Microphone","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Interdisciplinary Research in Music Media and Technology","funders":"McGill University","keywords":"Microphone; Classifier (UML); Noise reduction; Speech enhancement; Background noise; Noise measurement; Speech processing; Pattern recognition (psychology)","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":[0.00038248,0.0006202118,0.0007061276,0.0008761107,0.0002492698,0.0007168176,0.0004950664,0.0009928902,0.003912861],"category_scores_gemma":[0.001195705,0.0001505681,0.0005690424,0.0004060086,0.0001240678,0.0004786815,0.0004508052,0.0003693156,0.00327391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001993538,"about_ca_system_score_gemma":0.0002728577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006906856,"about_ca_topic_score_gemma":0.001319297,"domain_scores_codex":[0.9994749,0.00007856212,0.00002584118,0.0001268368,0.0002212119,0.00007254869],"domain_scores_gemma":[0.9995422,0.00009550494,0.00004449579,0.0000371566,0.0002472119,0.00003347523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001669376,0.0003134198,0.0337824,0.0004212279,0.0001808971,0.0009141248,0.000199614,0.005622146,0.1857966,0.0007972036,0.008545579,0.7617574],"study_design_scores_gemma":[0.0001677779,0.001625489,0.1828774,0.0001653564,0.0004577918,0.005123193,0.001081835,0.4808536,0.3009327,0.001534923,0.02500395,0.0001758025],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.700475,0.002878672,0.2703036,0.0005243971,0.001251367,0.0003022916,0.002945034,0.003906706,0.01741303],"genre_scores_gemma":[0.8486882,0.001695671,0.1279164,0.0003304089,0.0003967452,0.0001459636,0.00366083,0.0001736199,0.0169922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003912861,"threshold_uncertainty_score":0.01308984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0328788080915453,"score_gpt":0.2880354026864407,"score_spread":0.2551565945948954,"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."}}