{"id":"W2775169903","doi":"10.1371/journal.pntd.0006092","title":"Chagas disease vector control and Taylor's law","year":2017,"lang":"en","type":"article","venue":"PLoS neglected tropical diseases","topic":"Trypanosoma species research and implications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Environmental Health Sciences; Directorate for Mathematical and Physical Sciences; Fundación Mundo Sano; Fogarty International Center; International Development Research Centre; Universidad de Buenos Aires; National Institutes of Health; National Science Foundation; United Nations Development Programme; UNICEF","keywords":"Triatoma infestans; Triatoma; Vector (molecular biology); Triatominae; Abundance (ecology); Population density; Population; Biology; Ecology; Chagas disease; Habitat; Biodiversity; Reduviidae; Hemiptera; Demography; Trypanosoma cruzi","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001725329,0.0002744657,0.0003666561,0.0005345581,0.0002295721,0.0007820376,0.0005198501,0.000412157,0.001784527],"category_scores_gemma":[0.01204212,0.0001183053,0.0003512224,0.0004121853,0.002643622,0.001433395,0.0004278068,0.0006102814,0.0002280144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325491,"about_ca_system_score_gemma":0.0005608019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005106248,"about_ca_topic_score_gemma":0.00115545,"domain_scores_codex":[0.9991655,0.0003276402,0.00004743784,0.0001750899,0.0002184197,0.0000658993],"domain_scores_gemma":[0.9932887,0.004118295,0.001463076,0.000320914,0.0006695934,0.0001394174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002740035,0.0001818816,0.1641748,0.0006795818,0.0001903288,0.001276018,0.002154782,0.1834808,0.006287916,0.4881596,0.01493916,0.1382012],"study_design_scores_gemma":[0.00003938138,0.0003828222,0.1037956,0.0001802467,0.00006322255,0.001905749,0.0005660905,0.5809141,0.001865482,0.2969541,0.01325387,0.00007927442],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6490092,0.01697058,0.262338,0.01075062,0.0004428595,0.000129129,0.0004934905,0.0005910044,0.05927523],"genre_scores_gemma":[0.9949504,0.0007852916,0.003006285,0.000172219,0.0001008949,0.00001975534,0.00003871317,0.00001361307,0.0009127721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005106248,"threshold_uncertainty_score":0.01015306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02253279519201495,"score_gpt":0.2894271392578963,"score_spread":0.2668943440658813,"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."}}