{"id":"W3045984985","doi":"10.2196/18212","title":"Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis","year":2020,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Medical University","keywords":"mHealth; Digital health; The Internet; Popularity; Mobile phone; Library science; World Wide Web; Telemedicine; Health care; Internet privacy; Computer science; Medicine; Psychology; Telecommunications; Nursing; Political science; Psychological intervention","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics","sts"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.001655443,0.0006081722,0.001585213,0.02177598,0.00300165,0.00004100702,0.0003446779,0.0005140777,0.0006505537],"category_scores_gemma":[0.0001568834,0.0005232758,0.0001526912,0.07966673,0.0001778879,0.0001721395,0.0002030213,0.002000848,0.0001513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004062436,"about_ca_system_score_gemma":0.002626625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009290056,"about_ca_topic_score_gemma":0.0007087884,"domain_scores_codex":[0.9923631,0.001232912,0.002023739,0.001502236,0.0005649863,0.002313039],"domain_scores_gemma":[0.991356,0.0009715503,0.001128697,0.0007845993,0.0002404618,0.005518731],"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":[0.0004861902,0.0003397176,0.06059569,0.009177775,0.0001235383,0.000002545517,0.009979475,0.00002018555,0.000006807964,0.00983428,0.0558008,0.853633],"study_design_scores_gemma":[0.003013924,0.003039478,0.4751612,0.0001529835,0.000266388,0.000005398324,0.00254464,0.00191997,0.000001554511,0.0003333407,0.5130321,0.0005289907],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.880633,0.04024195,0.0006068618,0.05803588,0.0007257843,0.01138624,0.001504362,0.0009268095,0.005939139],"genre_scores_gemma":[0.9303004,0.01959522,0.0005850744,0.04231649,0.0009796728,0.005362879,0.0003594899,0.00008583577,0.0004149623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.853104,"threshold_uncertainty_score":0.9997219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09990733422089126,"score_gpt":0.4854177981160285,"score_spread":0.3855104638951373,"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."}}