{"id":"W1996142024","doi":"10.1038/srep00105","title":"The Impact of Demographic Variables on Disease Spread: Influenza in Remote Communities","year":2011,"lang":"en","type":"article","venue":"Scientific Reports","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Public Health Ontario; University of Toronto; Public Health Agency of Canada; University of Winnipeg","funders":"Canadian Institutes of Health Research; Mitacs; Compute Canada","keywords":"Disease; Population; Demography; Incidence (geometry); Indigenous; Immunity; Public health; Environmental health; Gerontology; Medicine; Biology; Immunology; Ecology; Immune system","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":[0.0009940559,0.0005650594,0.0006526094,0.0005253585,0.0007192365,0.001308454,0.0009707863,0.00113139,0.002701585],"category_scores_gemma":[0.00398276,0.0003660975,0.0007171931,0.0003369807,0.001037496,0.001339705,0.001381992,0.0009465349,0.0002500356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009525547,"about_ca_system_score_gemma":0.0008032692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04013753,"about_ca_topic_score_gemma":0.02658385,"domain_scores_codex":[0.9995795,0.0002558705,0.00001064612,0.0000551759,0.00002764425,0.00007121082],"domain_scores_gemma":[0.9986254,0.0007812101,0.0002540646,0.00004316732,0.00009103154,0.000205115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002523331,0.0003546583,0.06764305,0.00009923193,0.0001843726,0.001033208,0.0006729503,0.895201,0.001974435,0.02536358,0.0007651642,0.00645599],"study_design_scores_gemma":[0.00006816314,0.0002713506,0.02023482,0.00002687793,0.00008249603,0.0001408835,0.0005159896,0.970039,0.0001765794,0.007831169,0.000570292,0.00004242071],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787778,0.00031117,0.01479031,0.0009438705,0.00002918571,0.00005181806,0.0002231305,0.0000216044,0.004851061],"genre_scores_gemma":[0.9974669,0.0001784632,0.0009950766,0.00003811592,0.00001324594,0.00002178417,0.00004359127,0.000004593487,0.001238314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04013753,"threshold_uncertainty_score":0.07980782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2483358133235595,"score_gpt":0.4088221196616469,"score_spread":0.1604863063380875,"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."}}