{"id":"W4391294614","doi":"10.2196/48949","title":"Cocreating an Automated mHealth Apps Systematic Review Process With Generative AI: Design Science Research Approach","year":2024,"lang":"en","type":"review","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Business Finland; Science Foundation Ireland; European Commission","keywords":"Computer science; mHealth; Systematic review; Debugging; Process (computing); Generative grammar; Artificial intelligence; Scope (computer science); Data science; Software engineering; World Wide Web; Health care; MEDLINE; Programming language","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"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3708534,0.002857091,0.003948438,0.01937985,0.003664394,0.008154717,0.00473567,0.003495821,0.006122355],"category_scores_gemma":[0.506611,0.002555453,0.00613911,0.01357389,0.0060916,0.006452261,0.007360525,0.003212492,0.001610573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01201776,"about_ca_system_score_gemma":0.04304623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003586526,"about_ca_topic_score_gemma":0.009231381,"domain_scores_codex":[0.4404009,0.4876172,0.034142,0.0138741,0.02254022,0.001425588],"domain_scores_gemma":[0.2064843,0.7090223,0.02026449,0.03639499,0.02657422,0.001259643],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001388949,0.0006523336,0.004878747,0.1682204,0.004143573,0.001334565,0.07291086,0.01069637,0.008249325,0.06570061,0.008957624,0.6528667],"study_design_scores_gemma":[0.007486514,0.00493996,0.01041559,0.2392647,0.01811425,0.002658091,0.04164432,0.08748461,0.03575459,0.2583229,0.2922723,0.001642325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01898815,0.01082758,0.8220713,0.005823293,0.0007773247,0.1321133,0.00129981,0.001731358,0.006367917],"genre_scores_gemma":[0.03575213,0.001830873,0.8883042,0.0008842651,0.00007014884,0.0721422,0.0002757392,0.0001349279,0.00060552],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6291466,"threshold_uncertainty_score":0.7758498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4486247557437692,"score_gpt":0.6532317943544215,"score_spread":0.2046070386106523,"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."}}