{"id":"W4390654340","doi":"10.2196/43554","title":"The Impact of Wireless Emergency Alerts on a Floating Population in Seoul, South Korea: Panel Data Analysis","year":2024,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Panel data; Population; Computer science; Medical emergency; Computer security; Environmental health; Medicine; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.003184612,0.0005209998,0.000577207,0.0007590041,0.0005716812,0.000868283,0.001077564,0.0009126742,0.003942277],"category_scores_gemma":[0.004035886,0.0004433235,0.002138098,0.001613278,0.0004755476,0.000821389,0.001376217,0.001940021,0.0008045044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000926945,"about_ca_system_score_gemma":0.0008098215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05549979,"about_ca_topic_score_gemma":0.04333153,"domain_scores_codex":[0.9976785,0.001165138,0.0001454901,0.0005281594,0.0001530207,0.0003297635],"domain_scores_gemma":[0.9935914,0.002900223,0.001654271,0.0006927697,0.0006382468,0.0005229418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001313498,0.0001616004,0.9907745,0.00004353513,0.0008151725,0.0001471788,0.0002559691,0.003940891,0.0002349937,0.0001249812,0.001370442,0.001999469],"study_design_scores_gemma":[0.00001824198,0.0002441902,0.981113,0.00003094117,0.0004584544,0.00008508965,0.001712256,0.01521207,0.0002282748,0.0001500801,0.0007164744,0.00003092843],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908854,0.0001410982,0.001171446,0.0002784615,0.00001889917,0.00003686607,0.006962819,0.00001777947,0.0004871785],"genre_scores_gemma":[0.991729,0.00009579357,0.0005197958,0.0001214445,0.00001452084,0.00007524943,0.006854767,0.000006607689,0.00058287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05549979,"threshold_uncertainty_score":0.1103535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08824412857844635,"score_gpt":0.3733488105350409,"score_spread":0.2851046819565946,"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."}}