{"id":"W4386954149","doi":"10.1016/j.jacadv.2023.100613","title":"Mobile Health Fitness Interventions","year":2023,"lang":"en","type":"article","venue":"JACC Advances","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; McGill University Health Centre","funders":"Fonds de Recherche du Québec - Santé; McGill University; Alberta Innovates; Canadian Institutes of Health Research; McGill University Health Centre; Public Health Agency; Public Health Agency of Canada","keywords":"mHealth; Psychological intervention; Logistic regression; Personalization; Applied psychology; eHealth; Psychology; Promotion (chess); Affect (linguistics); Health promotion; Medicine; Gerontology; Health care; Computer science; Public health; Nursing; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001104267,0.0001538485,0.00034876,0.000225241,0.001778609,0.000006621139,0.0002544639,0.0001102792,0.0008934436],"category_scores_gemma":[0.0001613911,0.0001405379,0.0001248316,0.00102651,0.00006109976,0.0002147767,0.0001204361,0.0004980113,0.005363099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001796911,"about_ca_system_score_gemma":0.0005989752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001310816,"about_ca_topic_score_gemma":0.0004365879,"domain_scores_codex":[0.9970876,0.0003267783,0.0009681904,0.0003920782,0.0002198548,0.001005498],"domain_scores_gemma":[0.9980112,0.0004723848,0.0004239705,0.0004872647,0.0001286157,0.0004766144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003608454,0.0001652562,0.01598568,0.005014672,0.00001280157,0.000002880442,0.001845363,0.0001813106,0.00001273469,0.03296768,0.2948413,0.6489342],"study_design_scores_gemma":[0.0004573277,0.00020163,0.006766089,0.0003620412,0.000004223328,8.345287e-7,0.003004281,0.00008110589,0.000002901847,0.00880821,0.9801977,0.0001136225],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"protocol","genre_scores_codex":[0.209804,0.1940215,0.08419568,0.08160748,0.04078382,0.1278969,0.003036459,0.02396754,0.2346866],"genre_scores_gemma":[0.3508379,0.1063572,0.009396242,0.02237043,0.003448248,0.387313,0.001617914,0.0002629078,0.1183962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6853564,"threshold_uncertainty_score":0.999521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.10049179764216,"score_gpt":0.5395914197925937,"score_spread":0.4390996221504337,"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."}}