{"id":"W2485297274","doi":"10.1158/1538-7445.am2016-846","title":"Abstract 846: Improving T-cell receptor clonotyping of T-cell lymphomas using hybrid-Capture and next-generation sequencing","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"CAR-T cell therapy research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; Princess Margaret Cancer Centre; University Health Network; Calgary Laboratory Services","funders":"","keywords":"T-cell receptor; Biology; Sanger sequencing; T cell; Molecular biology; DNA sequencing; Gene rearrangement; Computational biology; Genetics; Gene","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":[0.001176693,0.000564114,0.0003454328,0.0007557901,0.0002618423,0.0008516869,0.000458015,0.0004907828,0.001767959],"category_scores_gemma":[0.001210195,0.0002482741,0.0004058489,0.0003933211,0.000259221,0.0002916741,0.0006421577,0.0004944491,0.001284949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002624081,"about_ca_system_score_gemma":0.0003844764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001056103,"about_ca_topic_score_gemma":0.002089035,"domain_scores_codex":[0.998965,0.0002793102,0.00006512636,0.0002898078,0.0003118612,0.00008883655],"domain_scores_gemma":[0.9994492,0.0001807231,0.00004954478,0.00007481052,0.0001990062,0.00004677832],"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":[0.00008715734,0.00003057497,0.004325557,0.00008225256,0.00002110149,0.00004022985,0.00004221476,0.001119762,0.9767773,0.0001548826,0.0003518724,0.0169671],"study_design_scores_gemma":[0.00001879347,0.0002085063,0.01823945,0.00001633736,0.00006194827,0.0004846572,0.00004472783,0.02663582,0.9478244,0.0003041884,0.0061333,0.00002789475],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6605834,0.001127073,0.3288913,0.000209053,0.00007778905,0.0003202318,0.002689646,0.002753973,0.003347611],"genre_scores_gemma":[0.6198754,0.0005492558,0.370175,0.0003194009,0.00004408235,0.0003057423,0.005634155,0.0004028241,0.002694101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001767959,"threshold_uncertainty_score":0.006223083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1702651020974911,"score_gpt":0.37797427230038,"score_spread":0.2077091702028889,"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."}}