{"id":"W2088847137","doi":"10.1016/j.ecolmodel.2013.06.028","title":"Use of growth functions to describe disease vector population dynamics—Additional assumptions are required and are important","year":2013,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Vector-Borne Animal Diseases","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Canada Research Chairs","keywords":"Logistic function; Population; Biology; Mortality rate; Population growth; Outbreak; Birth rate; Infectious disease (medical specialty); Generation time; Population dynamics; Demography; Mathematics; Statistics; Virology; Disease; Fertility; Medicine; Fecundity","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":[0.001999105,0.001408098,0.0008541095,0.0005583586,0.0006421057,0.001577548,0.002852237,0.002464135,0.003412327],"category_scores_gemma":[0.008559472,0.000571472,0.001395945,0.0005645001,0.0006675314,0.003610899,0.0009875454,0.002366598,0.003043633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009404859,"about_ca_system_score_gemma":0.0009773583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01405706,"about_ca_topic_score_gemma":0.005892915,"domain_scores_codex":[0.9994193,0.000257441,0.00004372064,0.00006750346,0.0001296954,0.00008224707],"domain_scores_gemma":[0.9976686,0.001245274,0.0003159569,0.0002537664,0.0004519503,0.00006445689],"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":[0.00003369822,0.00007319613,0.005150524,0.0002513516,0.00006664266,0.0003270093,0.0002419326,0.8865016,0.005832923,0.07448986,0.003251846,0.02377935],"study_design_scores_gemma":[0.000005230151,0.00001401924,0.0005670864,0.00003830932,0.00001417736,0.0001737297,0.00003763932,0.9785745,0.001342442,0.01481965,0.004395156,0.00001802064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0356443,0.0007353573,0.9443613,0.001593714,0.000264867,0.00009624783,0.0004613468,0.0003295805,0.01651343],"genre_scores_gemma":[0.7858217,0.002850081,0.172218,0.0005914247,0.0001971031,0.0004267842,0.001198102,0.0006463847,0.03605037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01405706,"threshold_uncertainty_score":0.02795053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06378134439738507,"score_gpt":0.2179724654652603,"score_spread":0.1541911210678752,"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."}}