{"id":"W4322752273","doi":"10.2196/35858","title":"Mobile Apps for Dietary and Food Timing Assessment: Evaluation for Use in Clinical Research","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institutes of Health; National Institute of General Medical Sciences; Harvard Catalyst; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Massachusetts General Hospital","keywords":"Usability; Mobile apps; App store; Computer science; Internet privacy; World Wide Web; Medicine; Human–computer interaction","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":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.06070104,0.0001449356,0.0003888754,0.001114222,0.002875632,0.00004392021,0.0002796655,0.0003734914,0.00005544801],"category_scores_gemma":[0.002928317,0.0001317249,0.00007981784,0.001739508,0.0002718696,0.0004849237,0.0003508876,0.002202968,0.0001742516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006283249,"about_ca_system_score_gemma":0.002357268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000121467,"about_ca_topic_score_gemma":0.0005574521,"domain_scores_codex":[0.9904743,0.004355509,0.001405377,0.0005998117,0.001193693,0.001971254],"domain_scores_gemma":[0.9738588,0.02260425,0.0001868975,0.0005106341,0.002343261,0.0004960935],"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":[0.0009531986,0.0007723591,0.05883151,0.007493223,0.00005072101,8.416963e-7,0.01646429,0.00003754892,0.00005771851,0.02849523,0.295231,0.5916124],"study_design_scores_gemma":[0.007707084,0.004919673,0.334591,0.0007168374,0.00001125614,6.209881e-7,0.02251209,0.1963792,0.000007675551,0.03792411,0.3949763,0.0002542303],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9190258,0.000414261,0.001579546,0.002878876,0.0004707068,0.07189515,0.000594033,0.0001577346,0.002983917],"genre_scores_gemma":[0.682301,0.001257377,0.001802007,0.0001669645,0.0002699998,0.3129821,0.0005306252,0.0000421998,0.0006477269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5913582,"threshold_uncertainty_score":0.9984225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6998562064075015,"score_gpt":0.7200615977443118,"score_spread":0.02020539133681032,"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."}}