{"id":"W4401730767","doi":"10.2196/52196","title":"Scientific Production Dynamics in mHealth for Diabetes: Scientometric Analysis","year":2024,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sistema Nacional de Investigadores","keywords":"mHealth; Scopus; Web of science; Citation; Scientometrics; Science Citation Index; China; Scientific literature; Health care; MEDLINE; Medicine; Political science; Library science; Computer science","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":[0.03120853,0.001064112,0.001913822,0.08907332,0.002108793,0.009099116,0.00114555,0.001027133,0.003301186],"category_scores_gemma":[0.1465614,0.000397429,0.003783166,0.1524556,0.001830605,0.005148247,0.003825272,0.0007634138,0.0007802526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004443365,"about_ca_system_score_gemma":0.006510108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006796444,"about_ca_topic_score_gemma":0.003835712,"domain_scores_codex":[0.9674931,0.01274301,0.003752873,0.002079359,0.01240556,0.001526162],"domain_scores_gemma":[0.8311846,0.1293783,0.01626198,0.005906056,0.01541454,0.001854477],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004033243,0.0003930521,0.7407345,0.004239663,0.002828556,0.0009324661,0.01254639,0.0204771,0.0009739447,0.01303418,0.00771743,0.1957195],"study_design_scores_gemma":[0.0001089082,0.0003820383,0.8505983,0.001146071,0.001160818,0.0007732138,0.02254987,0.07162626,0.001254381,0.02210208,0.02810591,0.0001920659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9417773,0.004951164,0.01656811,0.002088827,0.0001318032,0.001539818,0.009197337,0.0002032811,0.02354239],"genre_scores_gemma":[0.9812638,0.002205683,0.01040344,0.00006722992,0.0001516712,0.0009471815,0.004156662,0.00003409615,0.000770236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9687915,"threshold_uncertainty_score":0.1650485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04958711148149653,"score_gpt":0.4553042884120006,"score_spread":0.4057171769305041,"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."}}