{"id":"W2955745546","doi":"10.1145/3328927","title":"WearBreathing","year":2019,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Health Sciences Centre; University of Toronto; University Health Network; Sunnybrook Health Science Centre; Vector Institute","funders":"","keywords":"Respiratory rate; Accelerometer; Gyroscope; Computer science; Artificial intelligence; Real-time computing; Speech recognition; Heart rate; Medicine; Engineering","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":[0.0005410294,0.001625641,0.001087757,0.001248752,0.000445628,0.0007997993,0.001161137,0.0008284007,0.01123637],"category_scores_gemma":[0.003092059,0.0002532631,0.0007301102,0.0007423066,0.0002163265,0.0009697275,0.001182786,0.0005761432,0.008613121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002278444,"about_ca_system_score_gemma":0.0002787101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002632272,"about_ca_topic_score_gemma":0.007045351,"domain_scores_codex":[0.9990822,0.00009671188,0.0001040166,0.000317507,0.000302251,0.00009726101],"domain_scores_gemma":[0.998268,0.0003032451,0.0003234964,0.0004004493,0.0005196868,0.0001851469],"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":[0.003709325,0.001209549,0.1250637,0.003922458,0.000570042,0.001066722,0.0008436051,0.003428141,0.03343644,0.0007282192,0.1351704,0.6908513],"study_design_scores_gemma":[0.0003775882,0.003900592,0.6578512,0.000839157,0.0006299118,0.005085734,0.001626308,0.03166452,0.04686487,0.002199518,0.2485189,0.0004416445],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7202383,0.008380765,0.05632743,0.001110887,0.00210558,0.00218696,0.1196786,0.02881656,0.06115475],"genre_scores_gemma":[0.7411472,0.003670662,0.04295963,0.001437776,0.0005013873,0.001555758,0.139741,0.001333083,0.06765368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01123637,"threshold_uncertainty_score":0.03758943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005902699178919371,"score_gpt":0.2108765602531443,"score_spread":0.2049738610742249,"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."}}