{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001542928,0.0003392965,0.0005863847,0.0001363507,0.0002436744,0.00001608472,0.0005669147,0.000124591,0.0005817766],"category_scores_gemma":[0.0008030442,0.0002461224,0.0001359569,0.0004042152,0.001066918,0.0001338256,0.0003762616,0.0001740282,0.00005688794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006780087,"about_ca_system_score_gemma":0.0002485511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001179475,"about_ca_topic_score_gemma":0.005612717,"domain_scores_codex":[0.9975542,0.000502918,0.000588515,0.0007402563,0.0001463202,0.0004677285],"domain_scores_gemma":[0.9976988,0.0004809015,0.0003322278,0.001164627,0.0002067481,0.0001166745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002566181,0.002116895,0.9608384,0.0001345544,0.0003158935,0.00002633676,0.0001402595,0.02747805,0.001153165,0.0001542734,0.002634908,0.00244112],"study_design_scores_gemma":[0.001332065,0.0005110626,0.9659733,0.00007420024,0.0003044832,0.00000183615,0.0001210614,0.0307021,0.0002797809,0.00009446924,0.0002669463,0.0003386768],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910626,0.004397883,0.000711198,0.0004429143,0.000401759,0.0004490132,0.002425541,0.00005636668,0.00005272299],"genre_scores_gemma":[0.9983974,0.0001585307,0.00002759383,0.0002248664,0.00007875279,0.00004865439,0.0009934525,0.00002827656,0.00004250624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007334765,"threshold_uncertainty_score":0.9999991,"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."}}