{"id":"W4386215876","doi":"10.2196/51609","title":"Correction: Efficacy, Effectiveness, and Quality of Resilience-Building Mobile Health Apps for Military, Veteran, and Public Safety Personnel Populations: Scoping Literature Review and App Evaluation","year":2023,"lang":"en","type":"erratum","venue":"JMIR mhealth and uhealth","topic":"Resilience and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"","keywords":"Mobile apps; Resilience (materials science); Quality (philosophy); mHealth; Public health; Engineering; Psychology; Internet privacy; Computer science; Medicine; World Wide Web; Nursing; Psychological intervention","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01638938,0.003561123,0.003136437,0.006538751,0.004403124,0.00544595,0.004853698,0.01097069,0.06616598],"category_scores_gemma":[0.2596915,0.001734167,0.003664741,0.005066671,0.003855063,0.003964164,0.00360015,0.0139245,0.02487573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007010604,"about_ca_system_score_gemma":0.0183145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05394011,"about_ca_topic_score_gemma":0.05131699,"domain_scores_codex":[0.980019,0.003310235,0.00509219,0.001636212,0.008980214,0.0009622127],"domain_scores_gemma":[0.8595917,0.04830677,0.007893849,0.005238869,0.07677425,0.00219456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00005299247,0.00000635019,0.00007269515,0.0009525491,0.00003133098,0.0001180957,0.00008421919,0.00002431407,0.00002542779,0.0004044854,0.9927376,0.005489977],"study_design_scores_gemma":[0.0003511928,0.00007225314,0.001470344,0.01282489,0.0005020238,0.000713532,0.0004678415,0.0003435944,0.0006049552,0.002797274,0.9796805,0.0001716208],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"review","genre_scores_codex":[0.0001986385,0.00283785,0.0008506827,0.1013304,0.8862873,0.0001791878,0.004816696,0.0006230367,0.00287618],"genre_scores_gemma":[0.02472664,0.03707274,0.0129505,0.3351296,0.3861539,0.003596828,0.009007465,0.004312725,0.1870495],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.06616598,"threshold_uncertainty_score":0.2213473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.134169993562046,"score_gpt":0.5115330995620228,"score_spread":0.3773631059999767,"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."}}