{"id":"W4289012953","doi":"10.1101/2022.07.28.22278155","title":"Failure to balance social contact matrices can bias models of infectious disease transmission","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Social contact; Basic reproduction number; Demography; Transmission (telecommunications); Context (archaeology); Population; Incidence (geometry); Disease; Contact tracing; Infectious disease (medical specialty); Vaccination; Disease transmission; Medicine; Biology; Statistics; Mathematics; Immunology; Coronavirus disease 2019 (COVID-19); Virology; Computer science; Psychology; Social psychology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006568219,0.0007130638,0.0006800208,0.000915284,0.0007998167,0.00160474,0.001112989,0.001201553,0.003648042],"category_scores_gemma":[0.03053267,0.0006759698,0.001211762,0.0006055892,0.001528506,0.002285752,0.001592634,0.001303163,0.000401571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001653681,"about_ca_system_score_gemma":0.001092086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01746717,"about_ca_topic_score_gemma":0.01025691,"domain_scores_codex":[0.9967121,0.002092305,0.0001920403,0.000518674,0.0002419188,0.0002430139],"domain_scores_gemma":[0.987347,0.008241041,0.002118974,0.001278869,0.000689997,0.0003241056],"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":[0.000267715,0.000135048,0.07147986,0.0001554772,0.0004721042,0.000350677,0.0005589069,0.8582168,0.003073801,0.04596224,0.002209818,0.01711757],"study_design_scores_gemma":[0.00008198695,0.0001370239,0.01204051,0.00006734216,0.00008302882,0.0001445288,0.0003076316,0.923241,0.0007222335,0.06057804,0.002540752,0.00005593136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8085047,0.0005814669,0.1786578,0.002102358,0.0002161703,0.0002821193,0.001685856,0.0003244504,0.007645156],"genre_scores_gemma":[0.990564,0.00015856,0.00744599,0.0001938202,0.00003244774,0.00009816327,0.000337117,0.00003758222,0.001132348],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01746717,"threshold_uncertainty_score":0.03473651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.193272335509572,"score_gpt":0.3943207638414388,"score_spread":0.2010484283318668,"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."}}