{"id":"W4414240743","doi":"10.22541/au.175803349.96342915/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":"Transcriptome; Gene expression profiling; Host (biology); Gene; Profiling (computer programming); Gene expression","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":[0.0001423941,0.0002618676,0.0002339372,0.0005468801,0.0002513317,0.0002710083,0.0001423874,0.0002521423,0.0005429866],"category_scores_gemma":[0.0001542029,0.0001333713,0.0002969537,0.0003286015,0.0001697913,0.000211969,0.0002780925,0.0002957802,0.0001894114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002657373,"about_ca_system_score_gemma":0.0003186229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00257192,"about_ca_topic_score_gemma":0.005956581,"domain_scores_codex":[0.9999232,0.000005736254,0.000003305164,0.00003602116,0.00001961843,0.0000120419],"domain_scores_gemma":[0.9999094,0.00002205358,0.00001900188,0.000007498203,0.00002485792,0.00001716945],"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":[0.000120067,0.0000105068,0.01013585,0.00008122425,0.00002598287,0.00006617505,0.0001492711,0.0002224985,0.9855601,0.00007487582,0.00006224283,0.003491207],"study_design_scores_gemma":[0.00001311556,0.0002856688,0.7396798,0.00004091457,0.000129285,0.0006484364,0.0008067693,0.00680492,0.2462331,0.0004248051,0.004891902,0.00004140594],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897507,0.0008779929,0.003149222,0.00006388919,0.00001624515,0.0000235068,0.00514497,0.00006013001,0.0009133543],"genre_scores_gemma":[0.9793772,0.000648451,0.009416772,0.0001437947,0.0000157898,0.00008408125,0.008285763,0.00007506981,0.001953163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00257192,"threshold_uncertainty_score":0.005113959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02067506233412137,"score_gpt":0.2704257090269584,"score_spread":0.249750646692837,"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."}}