{"id":"W2793081850","doi":"10.1089/vbz.2017.2234","title":"High-Resolution Ecological Niche Modeling of <i>Ixodes scapularis</i> Ticks Based on Passive Surveillance Data at the Northern Frontier of Lyme Disease Emergence in North America","year":2018,"lang":"en","type":"article","venue":"Vector-Borne and Zoonotic Diseases","topic":"Vector-borne infectious diseases","field":"Immunology and Microbiology","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cegep de Saint Hyacinthe; Public Health Agency of Canada; McGill University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Ottawa","keywords":"Ixodes scapularis; Tick; Environmental niche modelling; Lyme disease; Geography; Ecology; Ixodes; Ecological niche; Biology; Habitat; Ixodidae","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005576677,0.0005634468,0.0003386545,0.000672078,0.0006194749,0.0007384708,0.0009248437,0.0004327016,0.0006054773],"category_scores_gemma":[0.001121705,0.0003783913,0.0007553412,0.0004055442,0.0004689714,0.0003153233,0.0004153863,0.000319116,0.00009406531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003299573,"about_ca_system_score_gemma":0.002516968,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5738868,"about_ca_topic_score_gemma":0.5073682,"domain_scores_codex":[0.999887,0.00002714315,0.000006655332,0.00003774568,0.00001187931,0.00002955586],"domain_scores_gemma":[0.9996501,0.0001782793,0.00004986853,0.00001583855,0.00006126399,0.00004471581],"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":[0.00008421387,0.0000565828,0.04878,0.00002366024,0.00006790357,0.00006278964,0.0001116787,0.9454381,0.0006912299,0.0002278993,0.0002454375,0.004210406],"study_design_scores_gemma":[0.00000525779,0.000006119979,0.007830213,0.000002691806,0.000006203953,0.000008267304,0.00002959899,0.9919098,0.00005085425,0.00008430294,0.00006307505,0.000003562243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926805,0.000108682,0.006046546,0.00008767394,0.000003691326,0.00001701677,0.0004799615,0.00009280237,0.0004831874],"genre_scores_gemma":[0.995896,0.00003374334,0.003206466,0.00001489381,0.000002820377,0.00001327113,0.000536971,0.000009841295,0.0002860309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4261132,"threshold_uncertainty_score":0.8572454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146621980413265,"score_gpt":0.231600652996768,"score_spread":0.2169384549554415,"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."}}