{"id":"W2969185598","doi":"10.1016/j.meegid.2019.103998","title":"Protein mass spectrometry detects multiple bloodmeals for enhanced Chagas disease vector ecology","year":2019,"lang":"en","type":"article","venue":"Infection Genetics and Evolution","topic":"Trypanosoma species research and implications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences; International Development Research Centre; National Science Foundation; National Institutes of Health; University of Vermont","keywords":"Triatominae; Chagas disease; Vector (molecular biology); Biology; Trypanosoma cruzi; Ecology; Proteomics; Tropical disease; Computational biology; Disease; Virology; Parasite hosting; Genetics; Computer science; Medicine; Hemiptera","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003413945,0.0001026605,0.0001461756,0.0001677667,0.0001190616,0.00002227429,0.00002953104,0.00008583151,0.00009082427],"category_scores_gemma":[0.0002420526,0.00009907108,0.00006615194,0.0001930026,0.00004621116,0.00004892375,0.00002177941,0.0001001026,0.00006971392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001460528,"about_ca_system_score_gemma":0.0001123367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002259973,"about_ca_topic_score_gemma":0.00004392601,"domain_scores_codex":[0.9991429,0.00002517691,0.0001600178,0.0002646756,0.000130872,0.0002763528],"domain_scores_gemma":[0.9992881,0.00004969748,0.00005798881,0.0002186013,0.0001627551,0.0002228182],"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":[0.0001829669,0.0001028336,0.0790173,0.0001250795,0.00002961877,3.889078e-7,0.00001010463,0.00002101006,0.9188581,0.0006060466,0.00008048514,0.0009661061],"study_design_scores_gemma":[0.001550301,0.0009557968,0.9092394,0.00002290043,0.00003304556,0.000006428491,0.000008101341,0.003350728,0.08185709,0.0009516531,0.001925397,0.00009912177],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9679907,0.0002601662,0.02900788,0.000430508,0.0001717483,0.00178977,0.00003183384,0.00005583388,0.0002615769],"genre_scores_gemma":[0.9965801,0.0001495771,0.001813205,0.00004149767,0.0002266656,0.0003212853,0.00003836538,0.00001730678,0.0008119907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.837001,"threshold_uncertainty_score":0.4040002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280166616208679,"score_gpt":0.273991358359236,"score_spread":0.2611896921971492,"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."}}