{"id":"W3213723875","doi":"10.2196/32918","title":"Supporting People With Type 2 Diabetes in the Effective Use of Their Medicine Through Mobile Health Technology Integrated With Clinical Care to Reduce Cardiovascular Risk: Protocol for an Effectiveness and Cost-effectiveness Randomized Controlled Trial","year":2021,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University","funders":"National Institute for Health and Care Research","keywords":"Medicine; Randomized controlled trial; Intervention (counseling); Type 2 diabetes; mHealth; Mobile phone; Test (biology); Population; eHealth; Clinical trial; Cost effectiveness; Family medicine; Health care; Psychological intervention; Physical therapy; Nursing; Diabetes mellitus; Risk analysis (engineering); Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04629321,0.007296289,0.0133573,0.003469584,0.004675208,0.006307601,0.00423532,0.008720185,0.07685765],"category_scores_gemma":[0.04478203,0.003675324,0.01196651,0.004783907,0.003731043,0.005274194,0.003420348,0.0117189,0.01037344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009082054,"about_ca_system_score_gemma":0.02136948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005680545,"about_ca_topic_score_gemma":0.009069468,"domain_scores_codex":[0.9683729,0.0184942,0.004669446,0.00182019,0.003491719,0.003151564],"domain_scores_gemma":[0.9820881,0.005320382,0.003399702,0.001774757,0.005520874,0.001896087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.7910362,0.01616564,0.001332775,0.08012461,0.008041063,0.0004797851,0.001157328,0.003179576,0.001805346,0.007119287,0.03091146,0.05864692],"study_design_scores_gemma":[0.9027822,0.01891477,0.002922623,0.01535311,0.003800796,0.00009128916,0.0004087379,0.002077518,0.0008586585,0.003937863,0.04867909,0.000173264],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.0005688361,0.0001907618,0.0004571592,0.0001196768,0.0001407704,0.9973394,0.0007542239,0.00003820387,0.000390957],"genre_scores_gemma":[0.0005337783,0.00009483154,0.0009335575,0.00006471873,0.00001447033,0.9981128,0.00009266163,0.000002280025,0.0001509199],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.07685765,"threshold_uncertainty_score":0.2571145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2352970023903414,"score_gpt":0.6339319818809859,"score_spread":0.3986349794906444,"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."}}