{"id":"W2318240467","doi":"10.2196/rehab.4511","title":"Novel Use of a Smartphone to Measure Standing Balance","year":2016,"lang":"en","type":"article","venue":"JMIR Rehabilitation and Assistive Technologies","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Accelerometer; Balance (ability); Acceleration; Repeated measures design; Physical medicine and rehabilitation; Sitting; Force platform; Computer science; Physical therapy; Simulation; Mathematics; Medicine; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003923321,0.0006720652,0.0004353709,0.0007220157,0.0001698517,0.0005865999,0.0005315226,0.0006621295,0.002851914],"category_scores_gemma":[0.001494311,0.0001891578,0.000315817,0.0002609429,0.0001536163,0.0005278587,0.0006922078,0.0002596163,0.0009985879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000148093,"about_ca_system_score_gemma":0.0001913464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005046598,"about_ca_topic_score_gemma":0.001115643,"domain_scores_codex":[0.9995597,0.00009689328,0.00004140482,0.00008926662,0.0001795198,0.00003316504],"domain_scores_gemma":[0.9992357,0.0002026744,0.00009772097,0.0000499729,0.0003613606,0.00005248915],"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":[0.001985139,0.0005501735,0.07390247,0.002268937,0.0002546335,0.002093259,0.0009833485,0.0005140936,0.3375974,0.000717711,0.01015627,0.5689766],"study_design_scores_gemma":[0.0009982365,0.01616141,0.5456706,0.001509494,0.001850039,0.03558211,0.002333283,0.0507389,0.2796285,0.001900968,0.06308446,0.0005419378],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.801802,0.007787489,0.1651054,0.001467487,0.0008508256,0.001545603,0.002322041,0.003141057,0.01597803],"genre_scores_gemma":[0.8760849,0.002128193,0.1129593,0.0007571354,0.0002628484,0.001154148,0.0007086734,0.00004791204,0.005896802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002851914,"threshold_uncertainty_score":0.009540558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04884651528395665,"score_gpt":0.3590624992958533,"score_spread":0.3102159840118967,"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."}}