{"id":"W2981099371","doi":"10.2196/15940","title":"Improving Medication Information Presentation Through Interactive Visualization in Mobile Apps: Human Factors Design","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Western University of Health Sciences; Claremont Graduate University; Chapman University","keywords":"Computer science; Presentation (obstetrics); Human–computer interaction; Mobile apps; Multimedia; Information visualization; Visualization; mHealth; World Wide Web; Internet privacy; Medicine; Artificial intelligence; Psychological intervention","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":[0.01220076,0.001483679,0.000519703,0.001056842,0.0008766013,0.0021831,0.0008573038,0.0007915839,0.005478048],"category_scores_gemma":[0.02135739,0.0005811163,0.0009788726,0.0005882691,0.0008736968,0.001124385,0.0013554,0.0007053303,0.0005266216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009687136,"about_ca_system_score_gemma":0.001699612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009198819,"about_ca_topic_score_gemma":0.001022518,"domain_scores_codex":[0.9925348,0.005354565,0.0005098259,0.0006200162,0.0007016849,0.0002792356],"domain_scores_gemma":[0.9795631,0.01592606,0.0008229885,0.0009410366,0.002327601,0.0004191633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00505065,0.00459669,0.02900295,0.008335731,0.0005724337,0.0007411736,0.03148746,0.01796752,0.08284507,0.00827577,0.007049426,0.8040751],"study_design_scores_gemma":[0.01422066,0.09775469,0.1594469,0.004963847,0.004850573,0.002376293,0.02818093,0.2427302,0.1970361,0.04454361,0.2023505,0.001545617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3602021,0.001210768,0.6081046,0.00101806,0.0002861845,0.01934855,0.0004863683,0.002319575,0.00702373],"genre_scores_gemma":[0.3817995,0.000504392,0.596149,0.0002276971,0.0000605239,0.01938752,0.0001793664,0.000141516,0.001550419],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01220076,"threshold_uncertainty_score":0.06452453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07878600953330926,"score_gpt":0.4401039361046444,"score_spread":0.3613179265713352,"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."}}