{"id":"W3094741969","doi":"10.3389/fvets.2020.584724","title":"When the Sum of the Parts Tells You More Than the Whole: The Advantage of Using Metagenomics to Characterize Bartonella spp. Infections in Norway Rats (Rattus norvegicus) and Their Fleas","year":2020,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Bartonella species infections research","field":"Immunology and Microbiology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Ministry of Agriculture; University of Saskatchewan; Ministry of Health","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Public Health Agency; Public Health Agency of Canada","keywords":"Bartonella; Biology; Flea; Metagenomics; Sanger sequencing; Population; Polymerase chain reaction; Microbiology; DNA sequencing; Zoology; Genetics; Gene","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001195435,0.0001949837,0.000303659,0.000191409,0.0006497583,0.00005259437,0.001279812,0.00008822995,0.0000685105],"category_scores_gemma":[0.0002729397,0.00009318077,0.0000910493,0.001504526,0.003813333,0.0002189133,0.0008594005,0.0005462206,0.00001312886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000855579,"about_ca_system_score_gemma":0.0002160137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001735006,"about_ca_topic_score_gemma":0.00005187286,"domain_scores_codex":[0.9980798,0.0005732609,0.0003873378,0.0003893166,0.0001169443,0.0004532996],"domain_scores_gemma":[0.9987549,0.0002332081,0.0001583479,0.0007309204,0.00008218478,0.00004048154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001167148,0.00007142957,0.0247323,0.00001733984,0.00003617557,0.000002963777,0.01032495,0.0007713915,0.9618806,0.00007472953,0.0006346551,0.001336747],"study_design_scores_gemma":[0.001470135,0.001673799,0.5944281,0.0002039797,0.000075929,0.0006027495,0.03677743,0.005428283,0.1602644,0.0003074262,0.1980646,0.0007031637],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924034,0.0009096244,0.000555265,0.003688838,0.001100115,0.0008025928,0.00008199945,0.000008304753,0.0004498516],"genre_scores_gemma":[0.9989943,0.0001563434,0.0001627135,0.0003184955,0.00002843829,0.00002568211,0.000002246027,0.00001207898,0.0002996913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8016162,"threshold_uncertainty_score":0.9988977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03552407821217016,"score_gpt":0.2735917085553318,"score_spread":0.2380676303431616,"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."}}