{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003007824,0.00008773049,0.0001647619,0.000197585,0.0007019734,0.00002851459,0.00014131,0.00003698543,0.000005878735],"category_scores_gemma":[0.00005088138,0.00007697559,0.000009864628,0.0004506469,0.00008449379,0.0001684986,0.00009486694,0.0003010514,6.846799e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036834,"about_ca_system_score_gemma":0.0005422521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001690231,"about_ca_topic_score_gemma":0.0000554371,"domain_scores_codex":[0.9976835,0.001023876,0.0004236098,0.0002947517,0.0003241983,0.0002500792],"domain_scores_gemma":[0.9990046,0.0002701158,0.0003592589,0.0001645446,0.0001418329,0.00005961871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003027092,0.0001675626,0.001511649,0.0009873708,0.00001450588,0.000003189527,0.02497066,0.0005644691,0.00008548299,0.6237933,0.001178837,0.3464203],"study_design_scores_gemma":[0.001373625,0.004538112,0.02980053,0.0001013638,0.00001211546,0.0001779392,0.0284397,0.9298305,0.00004201505,0.004449449,0.001060926,0.0001737077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4513187,0.001864476,0.5404221,0.002445331,0.0007205812,0.003024269,0.00001290929,0.00009493376,0.00009661478],"genre_scores_gemma":[0.996231,0.00008564477,0.002543294,0.0002193885,0.00001710949,0.0008789258,0.00001057214,0.000005956454,0.00000816292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.929266,"threshold_uncertainty_score":0.5399083,"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."}}