{"id":"W4243838434","doi":"10.1109/ccnc.2014.7111682","title":"iVS: an intelligent end-to-end vital sign capture platform using smartphones","year":2014,"lang":"en","type":"article","venue":"","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Bluetooth; Wireless; Bluetooth Low Energy; Reliability (semiconductor); Vital signs; End user; Communications system; Computer network; Embedded system; Throughput; Telecommunications; Operating system","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":[0.0003049943,0.0005940135,0.000451698,0.0007065635,0.0002011992,0.0005663967,0.001026571,0.000563439,0.00336426],"category_scores_gemma":[0.000647868,0.0003007264,0.00026505,0.0002147968,0.0002205321,0.0008201798,0.001108175,0.0004408768,0.001530431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002363149,"about_ca_system_score_gemma":0.0003177583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005936544,"about_ca_topic_score_gemma":0.0005397232,"domain_scores_codex":[0.999604,0.00005892036,0.00003482171,0.00005767228,0.0001836807,0.00006101162],"domain_scores_gemma":[0.9997086,0.00004821226,0.00004137672,0.00003749278,0.0001086968,0.00005562942],"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":[0.001714515,0.0003579604,0.009233241,0.001053504,0.0001585186,0.001977091,0.0006076531,0.006119579,0.3882467,0.01482143,0.05059354,0.5251163],"study_design_scores_gemma":[0.0005012433,0.005322763,0.02414945,0.0004817423,0.0003446855,0.006906121,0.0004421319,0.3053555,0.315104,0.005267166,0.3356764,0.0004487729],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.113195,0.002072858,0.8258187,0.0007853754,0.0006271084,0.001227958,0.001043113,0.0295561,0.02567372],"genre_scores_gemma":[0.7622979,0.001197325,0.2077892,0.0009890597,0.0002645787,0.0006303602,0.001806492,0.0003664529,0.0246587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00336426,"threshold_uncertainty_score":0.01125461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01814111074588682,"score_gpt":0.2238915627120184,"score_spread":0.2057504519661316,"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."}}