{"id":"W2905952024","doi":"10.2196/11447","title":"An Analytics Platform to Evaluate Effective Engagement With Pediatric Mobile Health Apps: Design, Development, and Formative Evaluation","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Institute for Clinical Evaluative Sciences; University Health Network; University of Toronto; SickKids Foundation; Hospital for Sick Children; Public Health Ontario","funders":"","keywords":"mHealth; Operationalization; Computer science; Analytics; Testbed; Formative assessment; Psychological intervention; Data science; Medicine; World Wide Web; Psychology; Nursing","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":[0.1109838,0.00222048,0.000978742,0.003260825,0.001199748,0.003426776,0.001836283,0.001467971,0.003789902],"category_scores_gemma":[0.1195836,0.0009719112,0.002900495,0.0015591,0.002349994,0.003170456,0.003646668,0.001933021,0.0008391876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002677953,"about_ca_system_score_gemma":0.009997384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000901281,"about_ca_topic_score_gemma":0.00130014,"domain_scores_codex":[0.9386875,0.04194163,0.005988888,0.002559048,0.009175586,0.00164729],"domain_scores_gemma":[0.8694763,0.07906918,0.008654597,0.007008706,0.03330047,0.002490701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.012296,0.02423905,0.06350162,0.0125041,0.001721389,0.0005254325,0.02470259,0.01113157,0.01615575,0.01159355,0.01371772,0.8079112],"study_design_scores_gemma":[0.02998221,0.2517315,0.201294,0.01795406,0.007187982,0.001171677,0.02877472,0.08621031,0.172511,0.0295119,0.1721238,0.001546761],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4927011,0.001319303,0.2302023,0.001548067,0.000759967,0.2568356,0.003596831,0.002309729,0.01072713],"genre_scores_gemma":[0.2535127,0.0008678253,0.5107644,0.000543224,0.0001476522,0.2305019,0.001517538,0.0003326841,0.001812102],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1109838,"threshold_uncertainty_score":0.5869452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1543804893955089,"score_gpt":0.5074236041122318,"score_spread":0.3530431147167228,"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."}}