{"id":"W4399401374","doi":"10.2196/52461","title":"Global Trends in mHealth and Medical Education Research: Bibliometrics and Knowledge Graph Analysis","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bibliometrics; mHealth; Data science; Computer science; Library science; Medicine; Nursing","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01398324,0.0007535653,0.002573269,0.184898,0.0009831337,0.005631079,0.001038212,0.001036362,0.00413431],"category_scores_gemma":[0.05943969,0.000287912,0.002960048,0.2636559,0.001052119,0.005041755,0.002039638,0.0006586434,0.0007172053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003381803,"about_ca_system_score_gemma":0.004985933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00666121,"about_ca_topic_score_gemma":0.006961633,"domain_scores_codex":[0.9864109,0.003812637,0.002834146,0.001216238,0.005285731,0.0004402722],"domain_scores_gemma":[0.9300323,0.04658192,0.01255719,0.001816508,0.008163691,0.0008483186],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003931331,0.0002113915,0.494975,0.04124232,0.005321144,0.0006747466,0.004226739,0.004495427,0.0007807813,0.009576732,0.02499738,0.4131053],"study_design_scores_gemma":[0.000157875,0.000361747,0.8243169,0.01356289,0.00641648,0.001962684,0.01071418,0.01941489,0.001729759,0.0223757,0.0987185,0.0002684519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5114434,0.3084424,0.01666036,0.01170021,0.0006283141,0.001632409,0.1040356,0.001192015,0.04426518],"genre_scores_gemma":[0.8498321,0.09791334,0.01770122,0.0004978233,0.0007305717,0.001444289,0.0300751,0.0001457615,0.00165978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9860168,"threshold_uncertainty_score":0.0739513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1144941263665324,"score_gpt":0.6039902159135522,"score_spread":0.4894960895470197,"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."}}