{"id":"W7117480291","doi":"10.1145/3714394.3750551","title":"Utilizing Speech as a Biosignal for Monitoring Respiratory Health and Beyond","year":2025,"lang":"","type":"article","venue":"","topic":"Respiratory and Cough-Related Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Biosignal; Wearable computer; Wearable technology; Health care; Disease; Lung function; Focus (optics); Natural (archaeology)","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":[0.0006846781,0.0006019814,0.0003805175,0.0007022972,0.0002497444,0.001458193,0.0004073402,0.0008016095,0.001492901],"category_scores_gemma":[0.002902962,0.0001900056,0.0004233077,0.0004076642,0.0006196328,0.001148196,0.0008261407,0.0007120004,0.0008640586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001800879,"about_ca_system_score_gemma":0.0004032011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008375615,"about_ca_topic_score_gemma":0.001211007,"domain_scores_codex":[0.999544,0.0001345575,0.00002334764,0.0001468919,0.000121383,0.00002977036],"domain_scores_gemma":[0.9990029,0.0006487916,0.00009248812,0.00009919697,0.0001210541,0.00003564262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005754655,0.0002457241,0.01355076,0.0008166212,0.0001916079,0.000383814,0.0009730365,0.02915351,0.1989467,0.01370662,0.004313122,0.737143],"study_design_scores_gemma":[0.00009336732,0.001439163,0.08607937,0.0008109631,0.0005027568,0.00338145,0.001287105,0.6062402,0.1538521,0.08240706,0.06361579,0.0002906602],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1774629,0.006412707,0.79505,0.001933827,0.0005893218,0.0001876514,0.001670851,0.001100059,0.01559277],"genre_scores_gemma":[0.794173,0.006497096,0.1910268,0.000642076,0.0007497075,0.0001354429,0.001220747,0.0001915782,0.005363454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001492901,"threshold_uncertainty_score":0.004994214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.066329514054402,"score_gpt":0.404892068643644,"score_spread":0.3385625545892419,"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."}}