{"id":"W101425453","doi":"10.1016/j.amepre.2011.01.008","title":"Mobile Health","year":2011,"lang":"en","type":"article","venue":"American Journal of Preventive Medicine","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":84,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Cancer Institute; University of California, San Diego; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"mHealth; Cyberinfrastructure; Quarter (Canadian coin); Mobile technology; Telecommunications; Computer science; Business; Internet privacy; Environmental health; Mobile computing; Data science; Geography; Medicine; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000644989,0.0006783996,0.0002836385,0.001879185,0.001302922,0.002667107,0.000800365,0.001434909,0.5218069],"category_scores_gemma":[0.002390547,0.0002477022,0.000414884,0.001230436,0.0003201099,0.001983057,0.002483527,0.00103283,0.3839796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005208264,"about_ca_system_score_gemma":0.001245485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002587765,"about_ca_topic_score_gemma":0.004205462,"domain_scores_codex":[0.9994053,0.00009629937,0.00002557612,0.0001070109,0.0002538397,0.0001119478],"domain_scores_gemma":[0.9985741,0.0002392774,0.00007877147,0.0002177048,0.0005331981,0.0003569053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007602965,0.0001120511,0.000923209,0.0001285902,0.000005324244,0.00009354028,0.0001459454,0.00003213019,0.001035998,0.005705136,0.6863947,0.3053473],"study_design_scores_gemma":[0.00001781772,0.00003665919,0.0016707,0.00006719028,0.000005570431,0.0001500081,0.0001255591,0.00008799829,0.0002392753,0.0009445864,0.9966475,0.000007088404],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.002798088,0.001276753,0.00387868,0.005504077,0.001507903,0.0002595563,0.005325153,0.00335454,0.9760953],"genre_scores_gemma":[0.01236119,0.001374864,0.002178175,0.003279192,0.0008625714,0.000214948,0.004253855,0.0003668283,0.9751084],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.5218069,"threshold_uncertainty_score":0.6820844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06580173288948336,"score_gpt":0.4613607952757763,"score_spread":0.3955590623862929,"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."}}