{"id":"W2294136539","doi":"","title":"Towards improved performance and compliance in healthcare using wearables and bluetooth technologies","year":2015,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Wearable computer; Bluetooth; Smartwatch; Computer science; Wearable technology; Health care; Domain (mathematical analysis); Corporate governance; Compliance (psychology); Human–computer interaction; Data science; Embedded system; Risk analysis (engineering); Wireless; Business; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002824083,0.0001380531,0.0001607108,0.0002677414,0.00008679798,0.0001129084,0.0001648776,0.0000773252,7.783586e-8],"category_scores_gemma":[0.0001140522,0.0001334803,0.000005792942,0.0005029087,0.0002170196,0.000424493,0.0001966156,0.0001525289,2.393246e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007789717,"about_ca_system_score_gemma":0.00004230764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002974133,"about_ca_topic_score_gemma":0.000004182735,"domain_scores_codex":[0.9992072,0.000003225793,0.0001354643,0.0002296683,0.0001286299,0.0002958299],"domain_scores_gemma":[0.9996868,0.00002052282,0.00001418301,0.0001387389,0.00007206036,0.00006767849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005701463,0.00001084506,0.06485713,0.0009395698,0.000009838679,0.00001438938,0.001494698,0.1382204,0.001771171,0.001085148,0.00003330919,0.7915578],"study_design_scores_gemma":[0.0001723386,0.00003878587,0.00767112,0.0001340343,0.000001370921,0.00003164014,0.00008011352,0.9892882,0.002176827,0.0000915861,0.0001383824,0.000175597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7050047,0.002203946,0.2916535,0.00005954853,0.0001799383,0.00008667757,0.000001231758,0.0008071266,0.000003330669],"genre_scores_gemma":[0.9247997,0.0003605695,0.07478991,0.00001933339,0.00001341675,0.000005158094,3.249191e-7,0.0000107613,7.966142e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8510678,"threshold_uncertainty_score":0.5443169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02597620681379306,"score_gpt":0.2307053926303006,"score_spread":0.2047291858165076,"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."}}