{"id":"W4293094566","doi":"10.1109/mdm55031.2022.00063","title":"A Mobility-based Recommendation System for Mitigating the Risk of Infection during Epidemics","year":2022,"lang":"en","type":"article","venue":"2022 23rd IEEE International Conference on Mobile Data Management (MDM)","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"TRIPS architecture; SAFER; Global Positioning System; Computer science; Risk analysis (engineering); Tracing; Infection risk; Infectious disease (medical specialty); Crowd sourcing; Internet privacy; Computer security; Business; Transport engineering; Data science; Disease; Medicine; Engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001351262,0.0008069816,0.001013605,0.001609482,0.001080108,0.001100437,0.001816933,0.001542055,0.002836727],"category_scores_gemma":[0.004113649,0.0004193058,0.0006142337,0.001111612,0.0002242949,0.001699145,0.001037381,0.0008457204,0.001771323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006462713,"about_ca_system_score_gemma":0.0008793091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0159812,"about_ca_topic_score_gemma":0.01610599,"domain_scores_codex":[0.9993768,0.0001062197,0.00009272352,0.0002070371,0.0001404893,0.00007677086],"domain_scores_gemma":[0.9981763,0.0005366068,0.000134251,0.000336047,0.0006215553,0.0001951254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002186978,0.001195009,0.05682386,0.0005894701,0.0005177087,0.001870745,0.00107994,0.0736789,0.06535724,0.005478729,0.04235282,0.7488686],"study_design_scores_gemma":[0.0001551224,0.0004547164,0.01181601,0.00005864107,0.0002706547,0.0007184542,0.0002623585,0.9530804,0.01360381,0.002738885,0.01671518,0.0001258483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2274031,0.001210063,0.7039803,0.001977882,0.0003971304,0.001303937,0.003099281,0.05087236,0.009755879],"genre_scores_gemma":[0.8139752,0.0004973021,0.1759851,0.000464766,0.0001350922,0.0003788788,0.002297596,0.0001906825,0.00607533],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0159812,"threshold_uncertainty_score":0.03177637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09038340800834833,"score_gpt":0.3655052957405905,"score_spread":0.2751218877322422,"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."}}