{"id":"W1969431122","doi":"10.2196/mhealth.4026","title":"mHealthApps: A Repository and Database of Mobile Health Apps","year":2015,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Institutes of Health; University of Texas Health Science Center at Houston","keywords":"mHealth; App store; World Wide Web; Computer science; JavaScript; Android (operating system); Mobile apps; Internet privacy; Multimedia; Database; Health care","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":[0.00901273,0.001666549,0.001875935,0.02537382,0.00167835,0.004923013,0.003340217,0.001390071,0.00715431],"category_scores_gemma":[0.04231958,0.001532282,0.001922868,0.02085508,0.0009698013,0.007939692,0.005306859,0.00189717,0.007554813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001418257,"about_ca_system_score_gemma":0.0102326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008234408,"about_ca_topic_score_gemma":0.01106897,"domain_scores_codex":[0.992925,0.00120898,0.002174238,0.001309026,0.002102247,0.0002804015],"domain_scores_gemma":[0.9533431,0.01838385,0.006708021,0.008965691,0.009824109,0.00277516],"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":[0.001385209,0.0007405928,0.07609442,0.01063265,0.001109821,0.001633479,0.005144623,0.003142332,0.008008532,0.01138231,0.3469628,0.5337632],"study_design_scores_gemma":[0.0005788052,0.0006034232,0.1488322,0.003946578,0.001353679,0.0021674,0.00214367,0.01572108,0.01332412,0.01207886,0.7984265,0.0008238375],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05315425,0.009057056,0.1123295,0.003413031,0.0005273162,0.005940834,0.7077565,0.08430061,0.02352091],"genre_scores_gemma":[0.08594947,0.005614181,0.2131971,0.0009982673,0.0004476354,0.0043119,0.6762031,0.007170686,0.006107617],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02537382,"threshold_uncertainty_score":0.04766446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.113234089533439,"score_gpt":0.4783022808840424,"score_spread":0.3650681913506034,"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."}}