{"id":"W3188140690","doi":"10.1111/1758-5899.12888","title":"COVID‐Apps: Misdirecting Public Health Attention in a Pandemic","year":2021,"lang":"en","type":"article","venue":"Global Policy","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Pandemic; Public health; Coronavirus disease 2019 (COVID-19); Isolation (microbiology); Phone; Telehealth; Business; Directive; Investment (military); Health care; Internet privacy; Medicine; Public relations; Economic growth; Disease; Political science; Telemedicine; Nursing; Infectious disease (medical specialty); Economics; Computer science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005396122,0.0001421542,0.0002111024,0.0001556763,0.0001125781,0.00042792,0.0004894273,0.00005858304,0.000006734764],"category_scores_gemma":[0.001403346,0.0001628169,0.00008626654,0.002133838,0.00001969121,0.0008478576,0.0003871529,0.0001466599,0.00006113074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002064389,"about_ca_system_score_gemma":0.003789176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005599742,"about_ca_topic_score_gemma":0.003907151,"domain_scores_codex":[0.9980376,0.0001715423,0.0003483568,0.0004957627,0.0002766258,0.0006700599],"domain_scores_gemma":[0.9988812,0.00009490384,0.000112385,0.0004610313,0.0000752382,0.0003752635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000005153357,0.0002339119,0.1487599,0.0001918335,0.00002876345,0.0001574837,0.001340415,0.0001018033,0.0004056797,0.1920814,0.001407013,0.6552866],"study_design_scores_gemma":[0.00455102,0.0002836348,0.746703,0.0007553573,0.000008541161,0.001089022,0.0009207399,0.02082059,0.0001370558,0.05566466,0.1673219,0.00174447],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4326347,0.002781865,0.2904476,0.2195479,0.001050284,0.0006719405,0.00005906203,0.001868707,0.05093799],"genre_scores_gemma":[0.984004,0.00002883082,0.001554812,0.01412741,0.000124736,0.000008410386,0.000007858271,0.000005978529,0.0001379717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6535422,"threshold_uncertainty_score":0.8465173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07367061228675542,"score_gpt":0.3679425127152235,"score_spread":0.2942719004284681,"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."}}