{"id":"W2482484925","doi":"10.1139/gen-2015-0179","title":"DNA barcodes identify medically important tick species in Canada","year":2016,"lang":"en","type":"article","venue":"Genome","topic":"Vector-borne infectious diseases","field":"Immunology and Microbiology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ontario Ministry of Agriculture, Food and Rural Affairs; Government of Canada; Ontario Genomics; Ontario Genomics Institute; Genome Canada","keywords":"Biology; Tick; Evolutionary biology; DNA barcoding; DNA; Genetics; Computational biology; Virology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0003281391,0.0002189136,0.0001728802,0.003029966,0.001658219,0.0006311255,0.0005486364,0.0002766422,0.001798609],"category_scores_gemma":[0.002030752,0.0001261656,0.0001255042,0.002965262,0.0005920517,0.0002378338,0.0004702911,0.0003334615,0.0002518549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01039448,"about_ca_system_score_gemma":0.01461816,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9452717,"about_ca_topic_score_gemma":0.9799518,"domain_scores_codex":[0.9992593,0.00002906011,0.00002445117,0.00007096289,0.0004413637,0.0001748982],"domain_scores_gemma":[0.9984945,0.0001109232,0.0002845723,0.0000261923,0.0008805881,0.0002031762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000482788,0.0001633678,0.64078,0.0004117283,0.00005983489,0.0006995421,0.004498674,0.00200471,0.1053674,0.002245342,0.007656809,0.2356299],"study_design_scores_gemma":[0.00001743168,0.0001123066,0.9450548,0.0001366533,0.00004054006,0.000533047,0.003987406,0.00370171,0.01570707,0.0003287407,0.03033741,0.00004300743],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792198,0.002489976,0.003196677,0.0005790693,0.00003587899,0.0001919482,0.003810055,0.0001268924,0.01034973],"genre_scores_gemma":[0.983072,0.001403587,0.009334645,0.0001748217,0.000007144715,0.0000308719,0.002499515,0.00002039959,0.003456968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05472827,"threshold_uncertainty_score":0.1101011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008821113714622847,"score_gpt":0.2125394664508246,"score_spread":0.2037183527362017,"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."}}