{"id":"W2897370809","doi":"10.2196/11898","title":"Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Physical Activity and Health","field":"Medicine","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council","keywords":"Activity tracker; Wearable computer; Internet privacy; Physical activity; Computer science; Smartphone application; mHealth; Wearable technology; Sampling (signal processing); Smartphone app; Applied psychology; Psychology; Multimedia; Psychological intervention; Medicine; Telecommunications; Physical medicine and rehabilitation","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":[0.04533471,0.0005877163,0.0009598287,0.003023968,0.001148685,0.002553804,0.001757278,0.001218971,0.00176631],"category_scores_gemma":[0.1409317,0.001119646,0.001570723,0.005375887,0.001554246,0.002361218,0.004185969,0.0009261522,0.0004388891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002821161,"about_ca_system_score_gemma":0.003169537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1345241,"about_ca_topic_score_gemma":0.1227807,"domain_scores_codex":[0.9188423,0.05249744,0.01130489,0.00523482,0.009771029,0.002349652],"domain_scores_gemma":[0.887709,0.03722543,0.03860439,0.01383782,0.02100982,0.001613633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008594654,0.00002122863,0.9875986,0.0002829809,0.0002349667,0.0001016593,0.001948817,0.0001017998,0.00009634611,0.0003913695,0.0006731481,0.008463157],"study_design_scores_gemma":[0.00003528973,0.0002378222,0.9899811,0.0005196393,0.0003508975,0.0003921482,0.002351653,0.001243773,0.0001893235,0.0001890096,0.004482473,0.00002675074],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686325,0.005446539,0.0125077,0.001985315,0.0002289793,0.001156594,0.003666666,0.00004276038,0.006333035],"genre_scores_gemma":[0.988964,0.001346614,0.005925133,0.0007966652,0.00005620605,0.001025389,0.001225858,0.0000261338,0.0006339886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1345241,"threshold_uncertainty_score":0.2674822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.139850039414155,"score_gpt":0.438378087929539,"score_spread":0.298528048515384,"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."}}