{"id":"W2046882251","doi":"10.3791/50643","title":"Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation","year":2013,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Chronic Obstructive Pulmonary Disease (COPD) Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital du Sacré-Cœur de Montréal","funders":"Fonds de Recherche du Québec - Santé; Canadian Lung Association","keywords":"Pulmonary rehabilitation; Medicine; Physical therapy; Aerobic exercise; Treadmill; Protocol (science); Attendance; Heart rate; Physical medicine and rehabilitation; Exercise intensity; Rehabilitation; Heart rate monitor; Computer science; Simulation; 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":[0.008770573,0.000535426,0.0006091683,0.001592479,0.0004989909,0.001198731,0.0006500522,0.001086711,0.001130579],"category_scores_gemma":[0.01595276,0.0003645101,0.000424638,0.002300558,0.0004864928,0.0007722728,0.000889701,0.0009452556,0.000321268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004313631,"about_ca_system_score_gemma":0.0008471851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002056899,"about_ca_topic_score_gemma":0.001898116,"domain_scores_codex":[0.9902501,0.005928238,0.0007277816,0.0009129902,0.001997577,0.00018335],"domain_scores_gemma":[0.9902357,0.005834586,0.001375283,0.001012903,0.00134979,0.0001917015],"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":[0.005320511,0.004764107,0.3433282,0.00216862,0.0008195274,0.0003251231,0.003677842,0.005041254,0.09269369,0.004502295,0.004445642,0.5329132],"study_design_scores_gemma":[0.0006585314,0.01987657,0.8538859,0.0005971729,0.0007601266,0.001146905,0.001374553,0.03616104,0.06808046,0.003288179,0.01387393,0.0002964963],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6148983,0.002989892,0.363676,0.000556189,0.0003895799,0.004000429,0.003780394,0.0007016932,0.009007629],"genre_scores_gemma":[0.7681078,0.00180132,0.2165943,0.0004562823,0.000235789,0.008372799,0.001643924,0.0001041355,0.002683572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008770573,"threshold_uncertainty_score":0.04638374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08176088560740315,"score_gpt":0.4917493429881521,"score_spread":0.409988457380749,"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."}}