{"id":"W2626150824","doi":"10.4236/etsn.2017.62002","title":"Validation of a Wearable Biometric System’s Ability to Monitor Heart Rate in Two Different Climate Conditions under Variable Physical Activities","year":2017,"lang":"en","type":"article","venue":"E-Health Telecommunication Systems and Networks","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Biometrics; Relative humidity; Wearable computer; Heart rate; Clothing; Heart rate monitor; Environmental science; Biometric data; Computer science; Simulation; Artificial intelligence; Medicine; Meteorology; Geography; Embedded system; Internal medicine","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":[0.001306428,0.0003394893,0.0002818161,0.0002783686,0.000167849,0.0003315279,0.0002160147,0.0004294993,0.001485015],"category_scores_gemma":[0.002776715,0.0001200831,0.0002012911,0.000246986,0.0002169253,0.0002928363,0.0003680377,0.0001969255,0.0005298548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007744152,"about_ca_system_score_gemma":0.0001360241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002997378,"about_ca_topic_score_gemma":0.0003646549,"domain_scores_codex":[0.9988059,0.0005189423,0.00008804784,0.0002490114,0.0002764026,0.00006176734],"domain_scores_gemma":[0.9985057,0.0005329537,0.0002030698,0.0002212937,0.0004454268,0.00009158573],"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":[0.005533903,0.001041054,0.1904213,0.0004213052,0.0002818038,0.0002411897,0.000911514,0.001391036,0.6929505,0.000308283,0.0006356618,0.1058625],"study_design_scores_gemma":[0.0002675249,0.01282775,0.8304545,0.00005563827,0.0002293177,0.001735694,0.0008553556,0.0133338,0.1379676,0.0001701948,0.002031197,0.00007133958],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880903,0.0001070959,0.01062749,0.0000312194,0.00005550416,0.00008199136,0.0002569455,0.00004640444,0.0007030533],"genre_scores_gemma":[0.9921107,0.00007360936,0.00681878,0.00004220352,0.00002064791,0.0001060433,0.0002210619,0.000009265561,0.0005976964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001485015,"threshold_uncertainty_score":0.006909132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02601375293575852,"score_gpt":0.3138861695385564,"score_spread":0.2878724166027978,"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."}}