{"id":"W1972606232","doi":"10.1603/me11210","title":"Passive Surveillance for I. scapularis Ticks: Enhanced Analysis for Early Detection of Emerging Lyme Disease Risk","year":2012,"lang":"en","type":"article","venue":"Journal of Medical Entomology","topic":"Vector-borne infectious diseases","field":"Immunology and Microbiology","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de Santé Publique du Québec; Cegep de Saint Hyacinthe; Public Health Agency of Canada","funders":"Public Health Agency of Canada","keywords":"Ixodes scapularis; Tick; Lyme disease; Biology; Population; Logistic regression; Veterinary medicine; Environmental health; Ecology; Ixodidae; Statistics; Virology; Medicine","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":[0.001095212,0.0004192069,0.0002996166,0.001148613,0.0001503615,0.0005261241,0.0003283835,0.0001571469,0.0008561177],"category_scores_gemma":[0.002278264,0.0001327938,0.0002189728,0.0007759879,0.0001369316,0.0002621806,0.0002590444,0.0001786043,0.0001840609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008359748,"about_ca_system_score_gemma":0.001024086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1458349,"about_ca_topic_score_gemma":0.2215346,"domain_scores_codex":[0.9997393,0.00008356918,0.00001138126,0.0000391552,0.0000918228,0.00003480968],"domain_scores_gemma":[0.9988751,0.0004169235,0.0002288367,0.00004485135,0.0003572424,0.00007709055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000521279,0.0001865528,0.9133428,0.0000973408,0.00009139674,0.00008845703,0.0002582692,0.00722396,0.01403015,0.0001407051,0.0007799143,0.06323921],"study_design_scores_gemma":[0.00001675452,0.0004021374,0.9102194,0.00001984164,0.00007476135,0.0001694433,0.0001816778,0.08409506,0.003874871,0.00009919631,0.0008246127,0.00002237517],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778777,0.0001737625,0.01903663,0.00005585627,0.000003683723,0.0001405239,0.0009960824,0.0002980765,0.001417577],"genre_scores_gemma":[0.9844898,0.0001010783,0.01415686,0.00001834123,0.000004740445,0.00003832541,0.0007465613,0.000007887314,0.0004365027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1458349,"threshold_uncertainty_score":0.2899721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009489794620727151,"score_gpt":0.2809541517191002,"score_spread":0.271464357098373,"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."}}