{"id":"W2729228834","doi":"10.2196/mhealth.7870","title":"Mobile Device Accuracy for Step Counting Across Age Groups","year":2017,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Physical Activity and Health","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute on Aging; University of Florida Health","keywords":"Wearable technology; Activity tracker; Wearable computer; Medicine; Physical medicine and rehabilitation; Body mass index; Activity monitor; Treadmill; Waist; Physical therapy; Physical activity; Gerontology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002183048,0.0005228429,0.0003531762,0.001249268,0.0003189818,0.0009482003,0.0005431913,0.0006720396,0.003914496],"category_scores_gemma":[0.01267395,0.0001710079,0.0007525897,0.0006895146,0.0001857307,0.0006440084,0.0008011608,0.0003000457,0.002088687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001899067,"about_ca_system_score_gemma":0.0001647492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001759073,"about_ca_topic_score_gemma":0.003644094,"domain_scores_codex":[0.997559,0.0006378357,0.000492576,0.0004907876,0.0006818718,0.0001379293],"domain_scores_gemma":[0.9923648,0.002322049,0.002158156,0.0006518835,0.002311095,0.0001920656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008850311,0.0001485809,0.945415,0.0002977464,0.0002025872,0.00007575763,0.0006256649,0.0002738201,0.001850466,0.0000941368,0.001539628,0.04859165],"study_design_scores_gemma":[0.00003139857,0.000818792,0.9909304,0.0001313994,0.0002214832,0.0004789986,0.0005029957,0.00152031,0.001860889,0.0001526922,0.003324947,0.00002576352],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785074,0.001730567,0.005084333,0.000186752,0.000132234,0.0004034641,0.005344196,0.0001784389,0.008432646],"genre_scores_gemma":[0.9887294,0.0004380565,0.006517345,0.0001508419,0.00004014518,0.0003247191,0.001976214,0.00002366035,0.00179955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003914496,"threshold_uncertainty_score":0.01309532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1262270127844724,"score_gpt":0.4772073759178642,"score_spread":0.3509803631333918,"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."}}