{"id":"W3038077244","doi":"10.1111/eva.13049","title":"Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens","year":2020,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Yersinia bacterium, plague, ectoparasites research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Centre for Disease Control; Government of British Columbia; Ministry of Agriculture; University of British Columbia; Ministry of Health","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Science Foundation","keywords":"Biology; Evolutionary biology; Ecology; Computational biology","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":[],"consensus_categories":[],"category_scores_codex":[0.00006495484,0.000147935,0.0001583591,0.0000541019,0.0002298986,0.00001411361,0.0002646992,0.0001512893,0.00004722933],"category_scores_gemma":[0.00009243461,0.0001747034,0.00009888882,0.0005722806,0.0001258116,0.0000056074,0.0001603814,0.0001082733,0.00004249864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001156355,"about_ca_system_score_gemma":0.0002081785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001484737,"about_ca_topic_score_gemma":0.000008502192,"domain_scores_codex":[0.9987119,0.00008811031,0.0002987666,0.0004224768,0.000189789,0.0002889406],"domain_scores_gemma":[0.9990181,0.00002440405,0.0000984397,0.0003749162,0.0002340861,0.0002500474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006769841,0.000170274,0.00939199,0.0000188434,0.00008954702,0.000003289503,0.00009857499,0.006274027,0.9805373,0.0002824188,0.002995426,0.00007063394],"study_design_scores_gemma":[0.004654493,0.002971711,0.2940459,0.0001455954,0.0007020044,0.0003903082,0.001467229,0.03863248,0.4880234,0.001446968,0.1640878,0.003432052],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8572522,0.000635337,0.1396229,0.0005640744,0.00003409903,0.0006800991,0.001033797,0.00003264221,0.0001448772],"genre_scores_gemma":[0.9941555,0.00004038926,0.004313227,0.0001170863,0.0001221652,0.00007660039,0.001071917,0.00002620061,0.00007690502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4925138,"threshold_uncertainty_score":0.7124197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03204891660037998,"score_gpt":0.2896292029413718,"score_spread":0.2575802863409918,"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."}}