{"id":"W7058399481","doi":"","title":"Nouvelles techniques de segmentation pour caractÃ©riser le timbre vocal d'un locuteur en vue de la vÃ©rification automatique de l'identitÃ©","year":2003,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Timbre; Segmentation; Mode (computer interface)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002234072,0.002073297,0.001243861,0.002445656,0.001691969,0.004782418,0.00187191,0.002686944,0.02877363],"category_scores_gemma":[0.005107227,0.001559559,0.002514855,0.001822139,0.002094625,0.00366098,0.002155281,0.003240756,0.02022828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001391369,"about_ca_system_score_gemma":0.001933097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005161802,"about_ca_topic_score_gemma":0.009555635,"domain_scores_codex":[0.9980261,0.0003081495,0.0001085753,0.000810022,0.0005651377,0.0001819587],"domain_scores_gemma":[0.9972712,0.001044412,0.0001952381,0.0006813203,0.0007117672,0.00009599721],"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":[0.0003766077,0.00005247015,0.00117874,0.000773788,0.0001314019,0.0002074592,0.001434349,0.006227343,0.2208232,0.02177857,0.006370578,0.7406454],"study_design_scores_gemma":[0.0001269289,0.0005847117,0.01467862,0.0008599585,0.0004212523,0.002072911,0.002090675,0.1784198,0.3929173,0.04285137,0.3646217,0.0003547576],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008699343,0.001538655,0.9757942,0.0003850385,0.0003009839,0.0001144262,0.0002330564,0.003161935,0.009772399],"genre_scores_gemma":[0.05168425,0.002155254,0.9128965,0.0003563457,0.0002131497,0.0002406846,0.0009954292,0.002192768,0.0292656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02877363,"threshold_uncertainty_score":0.09625739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001280089448763481,"score_gpt":0.1493013266958214,"score_spread":0.148021237247058,"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."}}