{"id":"W3093994489","doi":"10.2196/17577","title":"Evaluating Patient-Centered Mobile Health Technologies: Definitions, Methodologies, and Outcomes","year":2020,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"mHealth; CLARITY; Health care; Digital health; Patient satisfaction; Computer science; Data science; Medicine; Knowledge management; Psychological intervention; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.003022635,0.0005254503,0.001306946,0.0002779851,0.003392371,0.00002856439,0.0003059064,0.0004984158,0.000103067],"category_scores_gemma":[0.002265559,0.0004610803,0.00008606523,0.0007401189,0.00027039,0.0002025059,0.0004127265,0.001838355,0.000117169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004070441,"about_ca_system_score_gemma":0.003835809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005696794,"about_ca_topic_score_gemma":0.0001166055,"domain_scores_codex":[0.9914881,0.001994766,0.002345709,0.001258787,0.0005141402,0.002398485],"domain_scores_gemma":[0.9930136,0.002158612,0.001395946,0.0006986905,0.000232537,0.002500628],"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":[0.0002755642,0.00014314,0.03585041,0.008975819,0.00002227663,0.000002571348,0.006398594,0.000004062421,0.00001710879,0.01285621,0.0165399,0.9189144],"study_design_scores_gemma":[0.01141695,0.01249625,0.1090285,0.001173583,0.0001890746,0.000064661,0.07605748,0.002220387,0.00001462077,0.01620008,0.7694523,0.0016861],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6589932,0.05187042,0.002521849,0.2466593,0.00108963,0.03284327,0.0009343305,0.003721927,0.001366054],"genre_scores_gemma":[0.7448838,0.04741031,0.04416966,0.1246749,0.0002418783,0.03814244,0.0002734482,0.0001357762,0.00006786635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9172282,"threshold_uncertainty_score":0.9997841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4355863402892076,"score_gpt":0.5565044476215374,"score_spread":0.1209181073323298,"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."}}