{"id":"W4362521601","doi":"10.1038/s41564-023-01348-4","title":"Probe-based bacterial single-cell RNA sequencing predicts toxin regulation","year":2023,"lang":"en","type":"article","venue":"Nature Microbiology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; U.S. Department of Health and Human Services; National Institutes of Health; Harvard University","keywords":"Biology; Bacillus subtilis; Transcriptome; Escherichia coli; Clostridium perfringens; RNA; Context (archaeology); RNA-Seq; Gene; Computational biology; Bacterial genetics; Bacterial cell structure; Cell; Genetics; Gene expression; Bacteria","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":[0.0005103211,0.0003320359,0.0004145654,0.0002729248,0.0002339377,0.0006437344,0.000226907,0.0006268098,0.0008114285],"category_scores_gemma":[0.0008810591,0.0002443618,0.0003461161,0.0003071214,0.0003770891,0.0004663494,0.000320783,0.0006882994,0.0006238127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003868494,"about_ca_system_score_gemma":0.0002703005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006459188,"about_ca_topic_score_gemma":0.001757981,"domain_scores_codex":[0.999612,0.00004374984,0.00001626083,0.0001521414,0.0001345381,0.00004139514],"domain_scores_gemma":[0.9994709,0.0002467129,0.00008103452,0.00005663426,0.0001050019,0.00003979846],"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":[0.00002896517,0.000006728264,0.0007875111,0.00001802186,0.000003591584,0.000008290583,0.00001401694,0.0004022445,0.9966921,0.0001124175,0.00006245352,0.001863658],"study_design_scores_gemma":[0.000009239195,0.0001753516,0.01723782,0.000009663258,0.0000214128,0.00009689165,0.00007517593,0.02317167,0.9556624,0.0009857354,0.002530569,0.00002396213],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.833846,0.0007588015,0.156856,0.0004050171,0.00007663704,0.00007405403,0.004124191,0.001470793,0.002388416],"genre_scores_gemma":[0.913958,0.0007554584,0.07811891,0.0006011606,0.00003341135,0.0001523445,0.003729104,0.0003346628,0.002317021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008114285,"threshold_uncertainty_score":0.002806783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01054032399567986,"score_gpt":0.2357461131808092,"score_spread":0.2252057891851293,"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."}}