{"id":"W2943952292","doi":"10.3390/s19092164","title":"Smartphone Sensors for Health Monitoring and Diagnosis","year":2019,"lang":"en","type":"review","venue":"Sensors","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":440,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Health care; Life expectancy; Business; Population; Continuous monitoring; Risk analysis (engineering); Internet privacy; Medicine; Computer science; Environmental health; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001495123,0.0006350967,0.002958398,0.0003586788,0.001520482,0.00001584494,0.0002475965,0.0008807361,0.00008058389],"category_scores_gemma":[0.0004200489,0.0005534936,0.0003655487,0.000432351,0.00006650765,0.00004700893,0.0001283445,0.00143733,0.0009335606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006586467,"about_ca_system_score_gemma":0.002550605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003245031,"about_ca_topic_score_gemma":0.00004171184,"domain_scores_codex":[0.9939791,0.0009558705,0.002091936,0.001016336,0.0002704454,0.001686315],"domain_scores_gemma":[0.9919893,0.00437278,0.001501184,0.0009457992,0.0001787798,0.001012201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001051842,0.00003141444,0.0003671991,0.1487466,0.00004259703,7.047434e-7,0.0002587223,0.000001137905,1.240867e-8,0.0004061076,0.0192524,0.8308826],"study_design_scores_gemma":[0.000521699,0.0001098188,0.0001074643,0.01779803,0.0002204064,0.000005976567,0.0002478314,0.000009079236,1.086154e-7,0.00004183747,0.9805754,0.0003623274],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001529199,0.9736276,0.00001354761,0.001559724,0.002653446,0.02054119,0.0007000738,0.0002189236,0.0005325922],"genre_scores_gemma":[0.00000597286,0.9515393,0.001105803,0.0006277746,0.001793867,0.03976398,0.0002549089,0.000201997,0.004706351],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.961323,"threshold_uncertainty_score":0.9998443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.188111324571153,"score_gpt":0.5254837506810075,"score_spread":0.3373724261098545,"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."}}