{"id":"W4311577187","doi":"10.1002/2211-5463.13537","title":"High content quantitative imaging of <i>Mycobacterium tuberculosis</i> responses to acidic microenvironments within human macrophages","year":2022,"lang":"en","type":"article","venue":"FEBS Open Bio","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"HORIZON EUROPE Marie Sklodowska-Curie Actions; H2020 European Research Council; Medical Research Council; Horizon 2020 Framework Programme; European Commission; Wellcome Trust; Francis Crick Institute; Medical Research Council Canada; Cancer Research UK","keywords":"Phagosome; Intracellular; Mycobacterium tuberculosis; Biology; Biogenesis; Tuberculosis; Intracellular parasite; Macrophage; Pathogen; Cell biology; Microbiology; Host–pathogen interaction; Autophagy; Human pathogen; Cytosol; Mycobacterium; Computational biology; Bacteria; Virulence; Gene; Biochemistry; Medicine; Genetics; Pathology","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":[0.000531727,0.0002717766,0.0001382074,0.0004269787,0.0001698076,0.0003321185,0.0002595744,0.0006034008,0.001406577],"category_scores_gemma":[0.0003248224,0.0001956133,0.0001539274,0.0002334377,0.0002372156,0.0002660785,0.0002512536,0.0003308693,0.0002444555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002576264,"about_ca_system_score_gemma":0.0001832449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000595323,"about_ca_topic_score_gemma":0.0006837157,"domain_scores_codex":[0.9998592,0.00004474769,0.000008745057,0.00003266522,0.00002562928,0.00002908296],"domain_scores_gemma":[0.9998253,0.00007473141,0.00003002523,0.0000161637,0.00003712199,0.00001672546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008738468,0.00001068448,0.0002726814,0.00007017433,0.000004357116,0.00006011752,0.00002716713,0.000195534,0.9971663,0.0001533092,0.00009085659,0.001861336],"study_design_scores_gemma":[0.00001241185,0.0001234838,0.00547699,0.00002165633,0.0000235284,0.0005035888,0.00007503205,0.006692845,0.9844313,0.0001541964,0.002470845,0.00001413752],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8727542,0.005812044,0.111781,0.0007256676,0.00006245387,0.000146942,0.0009020385,0.0006361115,0.007179525],"genre_scores_gemma":[0.8783513,0.003177499,0.1123171,0.0003739853,0.00005367579,0.0002884766,0.0005625493,0.0001854367,0.004689948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001406577,"threshold_uncertainty_score":0.004705489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06462077700330543,"score_gpt":0.3588190746843442,"score_spread":0.2941982976810387,"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."}}