{"id":"W1973275696","doi":"10.1007/s11538-013-9918-2","title":"Estimating Initial Epidemic Growth Rates","year":2013,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":122,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; University of Victoria","funders":"","keywords":"Logistic function; Statistics; Epidemic model; Mathematics; Context (archaeology); Logistic regression; Confidence interval; Phenomenological model; Exponential function; Estimation theory; Econometrics; Applied mathematics; Demography; Population; Geography","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":[0.003263631,0.001177303,0.0009230442,0.002752434,0.000483928,0.001985406,0.00120532,0.001657532,0.001878717],"category_scores_gemma":[0.03437227,0.001053522,0.001059924,0.0007819683,0.0007409945,0.002307146,0.00138284,0.001862322,0.0007066365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001458421,"about_ca_system_score_gemma":0.0009023869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005666823,"about_ca_topic_score_gemma":0.003049545,"domain_scores_codex":[0.9993266,0.0003138066,0.00003366244,0.0001434828,0.00009117828,0.00009135715],"domain_scores_gemma":[0.9760272,0.0205994,0.0007529198,0.0009016274,0.001398005,0.0003208787],"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":[0.0003190046,0.000120634,0.0236398,0.0001508886,0.00009846657,0.0001779164,0.0002782416,0.8689763,0.00430087,0.02679646,0.001374571,0.07376678],"study_design_scores_gemma":[0.000008660247,0.00002477652,0.001306669,0.00001260008,0.00001414475,0.00003402051,0.00002902586,0.9848698,0.001817266,0.0116531,0.0002198087,0.00001003988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3170445,0.000447342,0.6760522,0.0004224858,0.00004354662,0.0001273033,0.0004258075,0.0006851709,0.00475169],"genre_scores_gemma":[0.9076291,0.0003477337,0.08799614,0.00004442615,0.0000482904,0.000112031,0.0007815048,0.00008168789,0.002959081],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005666823,"threshold_uncertainty_score":0.01725996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1787743908051966,"score_gpt":0.4264957255880282,"score_spread":0.2477213347828316,"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."}}