{"id":"W6966790545","doi":"10.5061/dryad.2n5h6","title":"Data from: The genetic signature of range expansion in a disease vector - the black-legged tick","year":2016,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tick; Genetic variation; Lyme disease; Tick-borne disease; Microsatellite; Biological dispersal; Range (aeronautics); Genetic structure; Genetic diversity","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004934773,0.0002093562,0.0001940371,0.001267623,0.0007372765,0.0007894434,0.000412254,0.0002802502,0.01909418],"category_scores_gemma":[0.002151749,0.0000967418,0.0001678775,0.00244018,0.0001987728,0.0002050482,0.0003122402,0.0002933384,0.003055987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002181686,"about_ca_system_score_gemma":0.003140472,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7086151,"about_ca_topic_score_gemma":0.8700922,"domain_scores_codex":[0.999604,0.00003998608,0.00003358628,0.00006929372,0.000178962,0.00007408672],"domain_scores_gemma":[0.9972656,0.0002825794,0.0004479942,0.0002034817,0.001491093,0.0003093855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005509984,0.0001074881,0.8764631,0.0003013311,0.0001437027,0.0003062593,0.0008686011,0.000601517,0.006813026,0.0002755104,0.05777691,0.0557917],"study_design_scores_gemma":[0.00003519115,0.00004093957,0.9673486,0.00007065207,0.00002821939,0.00008595385,0.0003180804,0.0004269393,0.0006582738,0.00003726147,0.03093586,0.00001417685],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.5821257,0.0008542122,0.001997,0.001228406,0.0001337334,0.0003011525,0.3835152,0.0003249235,0.02951969],"genre_scores_gemma":[0.7252259,0.000610519,0.004829345,0.0004773584,0.00007327654,0.0002223057,0.2465058,0.0000846184,0.02197083],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.7086151,"threshold_uncertainty_score":0.5862019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0290724289048121,"score_gpt":0.2697257752364359,"score_spread":0.2406533463316238,"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."}}