{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003612233,0.000117193,0.000219189,0.0001693266,0.00009486152,0.00002225707,0.00005498543,0.00009760358,0.0002029635],"category_scores_gemma":[0.00006379946,0.0001035981,0.00001800055,0.0002678178,0.00003168484,0.0008294765,0.00001558315,0.000206473,0.0001321254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001854402,"about_ca_system_score_gemma":0.0003157109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003629917,"about_ca_topic_score_gemma":0.00000782305,"domain_scores_codex":[0.9986483,0.0001084571,0.0005088202,0.0002086891,0.0002919454,0.000233766],"domain_scores_gemma":[0.9990833,0.00008317697,0.000382429,0.0001803383,0.00009950347,0.000171203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001817861,0.001459788,0.6749907,0.01560773,0.00006092421,0.000003774243,0.08830449,0.000231408,0.004758495,0.009937373,0.009730442,0.1930971],"study_design_scores_gemma":[0.005354109,0.002103067,0.9451638,0.0008176935,0.00005444986,0.00001309873,0.01415909,0.02323782,0.001240565,0.0007534481,0.00676408,0.0003388151],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725502,0.0002030163,0.02330159,0.0004131117,0.000160645,0.002287575,0.000003077521,0.00006396973,0.001016785],"genre_scores_gemma":[0.9971148,0.0003472251,0.0006295201,0.001158133,0.00005345288,0.0002597216,0.0002672566,0.000009309973,0.0001605143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2701731,"threshold_uncertainty_score":0.4224608,"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."}}