{"id":"W3067006404","doi":"10.1136/bmjopen-2019-034723","title":"mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE Study","year":2020,"lang":"en","type":"article","venue":"BMJ Open","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Agency for Healthcare Research and Quality","keywords":"Medicine; mHealth; Psychological intervention; Intervention (counseling); Depression (economics); Comorbidity; Mood; Randomized controlled trial; Patient Health Questionnaire; Clinical trial; Physical therapy; Diabetes mellitus; Psychiatry; Internal medicine; Depressive symptoms","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00596635,0.0001914281,0.0006611786,0.0000440661,0.001437899,0.00003943389,0.00047013,0.0001208154,0.00003289973],"category_scores_gemma":[0.003643374,0.0001289724,0.00005746679,0.0003262177,0.00003997283,0.0001416933,0.0009938597,0.001092578,0.0000270826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000723608,"about_ca_system_score_gemma":0.001184682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002233914,"about_ca_topic_score_gemma":0.0008978038,"domain_scores_codex":[0.9949811,0.002560703,0.0009330073,0.0006390387,0.0002355912,0.000650638],"domain_scores_gemma":[0.99413,0.00401906,0.0005128266,0.0004541355,0.00009074892,0.0007932158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.07336596,0.001867982,0.8402885,0.001520285,0.00002406827,0.00000240768,0.003703586,0.000107928,0.00002426317,0.00009923988,0.002633972,0.07636177],"study_design_scores_gemma":[0.1762134,0.00581641,0.4002135,0.0007758799,0.0001029127,5.915524e-7,0.003276793,0.300545,0.00001105796,0.0002147737,0.1122718,0.0005578863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.434762,0.000003367534,0.0003156402,0.003899394,0.00008414878,0.5607863,0.00001695933,0.00003505123,0.00009711814],"genre_scores_gemma":[0.2878361,0.000001617146,0.0004992381,0.00322546,0.001075565,0.7072867,0.000004130585,0.00002670415,0.00004443522],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.440075,"threshold_uncertainty_score":0.9998621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4392607605799874,"score_gpt":0.6421549815533069,"score_spread":0.2028942209733194,"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."}}