{"id":"W2968300229","doi":"10.1101/727917","title":"3D mapping of host-parasite-microbiome interactions reveals metabolic determinants of tissue tropism and disease tolerance in Chagas disease","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Trypanosoma species research and implications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; University of Oklahoma","keywords":"Chagas disease; Metabolomics; Biology; Metabolome; Disease; Microbiome; Pathogenesis; Trypanosoma cruzi; Megacolon; Immunology; Bioinformatics; Parasite hosting; Medicine; Pathology; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002020768,0.0002634939,0.0003040345,0.000598703,0.0002632481,0.0007409076,0.0001692109,0.0004319007,0.001789313],"category_scores_gemma":[0.0001726682,0.0002662181,0.0003651767,0.0004914131,0.0002465707,0.0003368433,0.0005297192,0.0004498415,0.0004383806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002410992,"about_ca_system_score_gemma":0.0002612964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00190538,"about_ca_topic_score_gemma":0.003876547,"domain_scores_codex":[0.999908,0.00001483777,0.00000320592,0.00002996358,0.00002298555,0.00002097242],"domain_scores_gemma":[0.9999336,0.00001406741,0.00001674598,0.000007403608,0.00001437146,0.00001383777],"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":[0.0003239333,0.00004053659,0.01288146,0.0002584766,0.0000828861,0.0001624189,0.0001811711,0.003737017,0.9643526,0.0008291025,0.001328204,0.01582219],"study_design_scores_gemma":[0.000093205,0.0004913791,0.4991099,0.0002257193,0.0002857475,0.00161002,0.002069421,0.1422181,0.3159427,0.005610083,0.03211388,0.0002297794],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9307109,0.003620024,0.05359649,0.0004749692,0.00008517735,0.00004412374,0.005995451,0.0007638661,0.004709006],"genre_scores_gemma":[0.9596476,0.001674486,0.0336519,0.0002181906,0.00002232757,0.00006258925,0.002977792,0.0001484622,0.001596687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00190538,"threshold_uncertainty_score":0.005985796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02051050649199109,"score_gpt":0.2884118433941046,"score_spread":0.2679013369021135,"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."}}