{"id":"W2732992419","doi":"10.1016/j.jneb.2018.02.002","title":"Mobile Apps for the Dietary Approaches to Stop Hypertension (DASH): App Quality Evaluation","year":2018,"lang":"en","type":"article","venue":"Journal of Nutrition Education and Behavior","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Illinois AMVETS; College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign; University of Illinois at Urbana-Champaign; Academy of Nutrition and Dietetics; AMVETS","keywords":"Dash; Inter-rater reliability; Mobile apps; App store; Reliability (semiconductor); Quality (philosophy); DASH diet; Smartphone app; Intraclass correlation; Medicine; Computer science; Psychology; Physical therapy; Internet privacy; Clinical psychology; World Wide Web; Psychometrics; Rating scale","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":[0.03168363,0.001245439,0.001639252,0.002256869,0.0009197491,0.002416597,0.0009591655,0.001710526,0.002930266],"category_scores_gemma":[0.125689,0.000662675,0.003091755,0.001234698,0.0008392264,0.002299073,0.002565495,0.001634323,0.0004928633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480574,"about_ca_system_score_gemma":0.003986426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003310229,"about_ca_topic_score_gemma":0.004371537,"domain_scores_codex":[0.9749102,0.0119912,0.004272561,0.00120125,0.006932339,0.0006925153],"domain_scores_gemma":[0.8942639,0.06794976,0.01126336,0.003117207,0.02121673,0.002188883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.107197,0.03080535,0.0757641,0.01606979,0.008751106,0.0002236737,0.006956931,0.0008069754,0.002134038,0.0007827719,0.009902887,0.7406054],"study_design_scores_gemma":[0.1088301,0.3683736,0.3476063,0.02513039,0.06830361,0.001193773,0.009884302,0.01176545,0.01417226,0.001946839,0.04173602,0.001057375],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589534,0.009557568,0.004044417,0.001463872,0.0004303292,0.01905923,0.002877104,0.0003986454,0.003215432],"genre_scores_gemma":[0.9238107,0.01036172,0.03109675,0.001451579,0.0003409854,0.0279041,0.002609527,0.0002053897,0.002219225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03168363,"threshold_uncertainty_score":0.167561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3690507636946064,"score_gpt":0.5157994862824105,"score_spread":0.146748722587804,"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."}}