{"id":"W3082570134","doi":"10.3390/s20174967","title":"A COVID-19-Based Modified Epidemiological Model and Technological Approaches to Help Vulnerable Individuals Emerge from the Lockdown in the UK","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Trent University; Nottingham Trent University","keywords":"Case fatality rate; Epidemiology; Coronavirus disease 2019 (COVID-19); Vulnerability (computing); Population; Epidemic model; Disease; Environmental health; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Demography; Susceptible individual; Medicine; Statistics; Computer science; Infectious disease (medical specialty); Mathematics; Computer security; Pathology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0007777384,0.0006706934,0.0007675501,0.0006607982,0.0004876716,0.001478198,0.001610304,0.002437978,0.004591618],"category_scores_gemma":[0.003173589,0.0004572571,0.001293488,0.0005906015,0.0005529283,0.0008561992,0.001467716,0.001122668,0.0005236484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482648,"about_ca_system_score_gemma":0.001391041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04394516,"about_ca_topic_score_gemma":0.01752828,"domain_scores_codex":[0.9994138,0.0003028304,0.00002943645,0.00007997551,0.00006432067,0.000109582],"domain_scores_gemma":[0.9990859,0.0005246337,0.0001409839,0.00003448969,0.0001384825,0.00007547812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009193103,0.00003826909,0.002077004,0.00004937659,0.00002377997,0.0002447889,0.00008234131,0.9850889,0.0004229142,0.008187779,0.0006596323,0.003033348],"study_design_scores_gemma":[0.00001911944,0.00004900668,0.0004947954,0.00001153197,0.00001584214,0.00003919678,0.00004599455,0.9967519,0.00005197278,0.00164761,0.0008612321,0.00001181578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4111567,0.002039868,0.5257638,0.005054273,0.0005032362,0.0006264279,0.003245152,0.0004987341,0.05111184],"genre_scores_gemma":[0.9376594,0.001021144,0.0362986,0.0002532655,0.00007285331,0.000427933,0.0008646937,0.00004143201,0.02336068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04394516,"threshold_uncertainty_score":0.08737874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2681341749205572,"score_gpt":0.3060474115501728,"score_spread":0.03791323662961554,"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."}}