{"id":"W2144731487","doi":"10.1016/j.jtbi.2005.01.013","title":"Scaling properties of childhood infectious diseases epidemics before and after mass vaccination in Canada","year":2005,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Measles; Population; Vaccination; Rubella; Outbreak; Scaling; Medicine; Immunology; Virology; Mathematics; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001644796,0.0002734186,0.0006761734,0.001618108,0.002256728,0.002416539,0.001510936,0.0007219019,0.004417705],"category_scores_gemma":[0.01168664,0.0003363818,0.0007058349,0.002235096,0.001330183,0.0007225733,0.0008255262,0.001209423,0.0002020753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0428942,"about_ca_system_score_gemma":0.03057692,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.992679,"about_ca_topic_score_gemma":0.9902345,"domain_scores_codex":[0.9991417,0.00008985942,0.00002253571,0.0001235692,0.0001416723,0.0004806969],"domain_scores_gemma":[0.9943044,0.00151697,0.0006784119,0.000252312,0.002090393,0.001157434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001031383,0.0001551145,0.885846,0.0001208719,0.0003911674,0.0004622422,0.005522585,0.04671909,0.001907007,0.0214818,0.01234868,0.02401404],"study_design_scores_gemma":[0.00003796272,0.00004284421,0.9471563,0.00004150426,0.00008416913,0.00007075493,0.00272144,0.04426441,0.0003173473,0.002404868,0.002786088,0.00007237181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936971,0.0007793267,0.0003957634,0.001348559,0.00001898042,0.00001903981,0.001432772,0.00002792217,0.002280585],"genre_scores_gemma":[0.998145,0.0002081658,0.00009153344,0.00003934305,0.000005300189,0.000004068314,0.000499754,0.000007052003,0.0009997434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0428942,"threshold_uncertainty_score":0.3112206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806714761721785,"score_gpt":0.3132544688132246,"score_spread":0.2851873211960068,"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."}}