{"id":"W4413968076","doi":"10.22541/au.175692147.71651283/v1","title":"Metatranscriptomic Profiling of Host-Microbiome Interactions in the Telencephalon and Liver of Carollia perspicillata","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fundação para a Ciência e a Tecnologia; Universidade Federal do Pará; Universidade de Lisboa; Fundação Amazônia Paraense de Amparo à Pesquisa; Fundação Amparo e Desenvolvimento da Pesquisa; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Financiadora de Estudos e Projetos; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; “la Caixa” Foundation","keywords":"Biology; Microbiome; Host (biology); Profiling (computer programming); Metagenomics; Zoology; Computational biology; Evolutionary biology; Ecology; Genetics; Gene; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001256153,0.0002280031,0.0001924595,0.0004916433,0.0002357916,0.0002474342,0.0001217798,0.0002226425,0.0006232962],"category_scores_gemma":[0.0001537252,0.0001216284,0.0002653909,0.0002970418,0.0001623163,0.0001990257,0.000268761,0.0002612197,0.0001898656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002476028,"about_ca_system_score_gemma":0.0003272603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00263153,"about_ca_topic_score_gemma":0.00560813,"domain_scores_codex":[0.9999257,0.000005513134,0.000003383959,0.0000355698,0.0000183927,0.00001150261],"domain_scores_gemma":[0.9999198,0.00002241299,0.00001631262,0.000007226151,0.00002034085,0.00001381658],"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":[0.0001284377,0.000009816188,0.01346708,0.00007461864,0.00002227885,0.0000616473,0.0001517025,0.0003262536,0.9810767,0.00008963464,0.00007568198,0.00451628],"study_design_scores_gemma":[0.00001252586,0.0002186179,0.7257522,0.00003286734,0.00009577452,0.0005004963,0.0006991161,0.008241299,0.2597299,0.0004321425,0.004246952,0.00003810065],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99182,0.0005050817,0.002857281,0.00005463503,0.00001125348,0.00001452632,0.003870185,0.00005831208,0.0008087655],"genre_scores_gemma":[0.9819904,0.0004784004,0.008700387,0.0001093957,0.00001296857,0.00006712512,0.006611577,0.00007563393,0.001953974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00263153,"threshold_uncertainty_score":0.005232453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02234272711942731,"score_gpt":0.2724438519782359,"score_spread":0.2501011248588086,"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."}}