{"id":"W4392847906","doi":"10.2196/52688","title":"New Approach to Equitable Intervention Planning to Improve Engagement and Outcomes in a Digital Health Program: Simulation Study","year":2024,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Verily Life Sciences","keywords":"Psychological intervention; Dropout (neural networks); Intervention (counseling); Digital health; Outcome (game theory); Resource allocation; Computer science; Resource (disambiguation); Process management; Medicine; Business; Health care; Nursing; Machine learning; Economics; Microeconomics","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":[0.003872513,0.0009758036,0.001069178,0.0008519941,0.000581424,0.001406586,0.001489461,0.002236793,0.006957906],"category_scores_gemma":[0.01307502,0.0004947739,0.001185141,0.0007839414,0.001180665,0.001476169,0.001945177,0.00232642,0.0002214082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002245563,"about_ca_system_score_gemma":0.003130925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02308296,"about_ca_topic_score_gemma":0.01463638,"domain_scores_codex":[0.9985455,0.000946484,0.00004556604,0.0001639833,0.00007743022,0.0002210406],"domain_scores_gemma":[0.9869369,0.0108167,0.0007274054,0.0003504449,0.0005060931,0.0006623812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001146866,0.0002211135,0.00243052,0.00004329912,0.00003989385,0.00004978278,0.00006995902,0.9891242,0.00007327281,0.005379085,0.000256466,0.002197686],"study_design_scores_gemma":[0.00009131186,0.0001069077,0.000332977,0.00001448182,0.00002060336,0.000006950779,0.00006458878,0.9964479,0.00007398067,0.002478685,0.0003548374,0.00000672716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.73428,0.0006461765,0.2369312,0.003839663,0.0001696928,0.0008637829,0.001218764,0.0002367323,0.02181382],"genre_scores_gemma":[0.965861,0.0002028389,0.03038709,0.0002576791,0.00002486497,0.0005828392,0.0002401167,0.00001899996,0.002424483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02308296,"threshold_uncertainty_score":0.04589725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1545768654440606,"score_gpt":0.516135049651501,"score_spread":0.3615581842074405,"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."}}