{"id":"W4367297040","doi":"10.1101/2023.04.24.538037","title":"FUME-TCRseq: Sensitive and accurate sequencing of the T-cell receptor from limited input of degraded RNA","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research; Institute of Infection and Immunity","funders":"CRIS Cancer Foundation; Rosetrees Trust; University College London Hospitals NHS Foundation Trust; National Institute for Health and Care Research; Cancer Research UK","keywords":"RNA; T-cell receptor; Computational biology; Biology; Digital polymerase chain reaction; Deep sequencing; T cell; Gene; Immune system; Genome; Polymerase chain reaction; Genetics","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":[0.002159756,0.0009985513,0.0007321987,0.0007992074,0.0003928995,0.00111398,0.0007686689,0.0007939145,0.001776673],"category_scores_gemma":[0.0029489,0.0005919952,0.0007648938,0.0003784365,0.0006944209,0.0004318389,0.0008967679,0.001220185,0.002250068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003845644,"about_ca_system_score_gemma":0.0005354888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006725422,"about_ca_topic_score_gemma":0.002195827,"domain_scores_codex":[0.9971704,0.0006595612,0.0001834496,0.000878126,0.0009220299,0.0001865993],"domain_scores_gemma":[0.9979492,0.0008115349,0.0003681626,0.0003876897,0.0003913718,0.00009205556],"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":[0.00008504858,0.00001700117,0.0006393318,0.0001421391,0.00003635074,0.00005964777,0.00005285543,0.001070441,0.9905775,0.0002606102,0.0005719904,0.006487109],"study_design_scores_gemma":[0.00002271146,0.0002933832,0.003822442,0.00004004296,0.00004311789,0.000278621,0.00004683988,0.01869581,0.9664249,0.000345473,0.009939769,0.00004689204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2877365,0.002338816,0.6892045,0.0003001836,0.0002557317,0.0005241408,0.00935064,0.007154109,0.003135337],"genre_scores_gemma":[0.4752754,0.001289485,0.4991598,0.0006461135,0.0001215947,0.0007474169,0.01608468,0.001648621,0.005026872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002159756,"threshold_uncertainty_score":0.01142204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01858986751581816,"score_gpt":0.2290014278726669,"score_spread":0.2104115603568487,"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."}}