{"id":"W4295751217","doi":"10.2196/40576","title":"The Intersection of Persuasive System Design and Personalization in Mobile Health: Statistical Evaluation","year":2022,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"mHealth; Personalization; Persuasive technology; Psychology; Applied psychology; Persuasion; Mobile technology; Affect (linguistics); Computer science; Multimedia; Mobile device; Social psychology; World Wide Web; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1408883,0.001038262,0.00194138,0.00473217,0.0009512795,0.002612128,0.001396393,0.00156488,0.006447244],"category_scores_gemma":[0.3095124,0.0005625833,0.00422507,0.003815345,0.00228817,0.003024661,0.00293466,0.001583246,0.000598243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002398992,"about_ca_system_score_gemma":0.003378609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001705468,"about_ca_topic_score_gemma":0.001077002,"domain_scores_codex":[0.8304499,0.1426138,0.009033742,0.003995337,0.01232317,0.001584072],"domain_scores_gemma":[0.4496395,0.4994658,0.01584946,0.01208977,0.0204983,0.002457117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.1153705,0.01863208,0.1997973,0.005730526,0.00627414,0.0001414227,0.008851154,0.01319471,0.001657422,0.01038387,0.005441588,0.6145253],"study_design_scores_gemma":[0.02868871,0.2374006,0.4354987,0.00239117,0.01822804,0.0005451767,0.009701264,0.2086149,0.01621494,0.01723375,0.02477479,0.0007080664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.875497,0.003376967,0.08074741,0.0006478236,0.0004316285,0.02768731,0.001281368,0.001248997,0.00908145],"genre_scores_gemma":[0.8988145,0.0006531338,0.06509343,0.0001622473,0.0001641647,0.03272449,0.0004147163,0.0002076989,0.001765664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1408883,"threshold_uncertainty_score":0.7450977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07207719888254482,"score_gpt":0.3996020704322806,"score_spread":0.3275248715497358,"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."}}