{"id":"W3209369207","doi":"10.2196/32093","title":"Mobile Apps Leveraged in the COVID-19 Pandemic in East and South-East Asia: Review and Content Analysis","year":2021,"lang":"en","type":"review","venue":"JMIR mhealth and uhealth","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Timeline; Pandemic; East Asia; Mainland China; Descriptive statistics; Public health; Content analysis; Coronavirus disease 2019 (COVID-19); Advertising; China; Geography; Business; Internet privacy; Medicine; Computer science; Nursing; Sociology; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004031226,0.000592322,0.003151695,0.0007375372,0.0002600862,0.0003340689,0.0006965538,0.0002628307,0.000005700305],"category_scores_gemma":[0.0003608491,0.0004307694,0.0002531798,0.002867448,0.00009780908,0.000335506,0.0004072423,0.001197236,0.000003175848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005734104,"about_ca_system_score_gemma":0.002549564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005863549,"about_ca_topic_score_gemma":0.001757862,"domain_scores_codex":[0.994086,0.001731082,0.001556424,0.001375914,0.0004317421,0.0008187889],"domain_scores_gemma":[0.9965823,0.0009043186,0.0007092466,0.0009392896,0.00005898619,0.0008058789],"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":[0.000006773153,0.00009504273,0.004519487,0.1642966,0.00008839527,0.0001124329,0.005174921,0.00000211539,1.245663e-8,0.0007577175,0.0001621134,0.8247844],"study_design_scores_gemma":[0.001683582,0.0004185587,0.005957459,0.03063515,0.002286936,0.0008411959,0.001818567,0.0004144549,3.308e-9,0.0001148408,0.9545857,0.001243542],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003377311,0.9932619,0.001508932,0.001560997,0.0000599595,0.003070745,0.00007580171,0.00005830472,0.00006557475],"genre_scores_gemma":[0.009283324,0.9799287,0.0001391469,0.009757476,0.00004859682,0.0007228142,0.00006262001,0.00002296159,0.00003441006],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9544236,"threshold_uncertainty_score":0.9998144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2848845167901434,"score_gpt":0.4375381594031497,"score_spread":0.1526536426130063,"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."}}