{"id":"W4396612526","doi":"10.1002/cyto.b.22175","title":"<scp>TRBC1</scp> in flow cytometry: Assay development, validation, and reporting considerations","year":2024,"lang":"en","type":"article","venue":"Cytometry Part B Clinical Cytometry","topic":"Cutaneous lymphoproliferative disorders research","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital","funders":"","keywords":"Flow cytometry; Computer science; Flow (mathematics); Cytometry; Computational biology; Medicine; Immunology; Biology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01145578,0.0006391726,0.001712239,0.003936057,0.000400858,0.0006091979,0.0002414161,0.0007380822,0.0006954831],"category_scores_gemma":[0.1026042,0.0006001138,0.0003997575,0.007445303,0.0006203585,0.0004676414,0.0004293675,0.001926026,0.0006917243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000505691,"about_ca_system_score_gemma":0.001898692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000021456,"about_ca_topic_score_gemma":0.00003618719,"domain_scores_codex":[0.9899561,0.0007436376,0.004714852,0.001832477,0.001527758,0.00122516],"domain_scores_gemma":[0.9832758,0.01286849,0.0008453932,0.001081444,0.0008138991,0.00111503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006373894,0.0007738643,0.953135,0.0007152213,0.0005666148,0.002562913,0.0005506363,0.00001419223,0.001751052,0.0002174979,0.01970574,0.01994359],"study_design_scores_gemma":[0.008754109,0.001659359,0.6821346,0.002881198,0.0006161191,0.01115175,0.002945346,0.01485884,0.02504703,0.00221175,0.2462683,0.00147166],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742559,0.004587715,0.005681115,0.001174226,0.001039724,0.001404573,0.00006396093,0.000578757,0.01121398],"genre_scores_gemma":[0.9816923,0.0006477837,0.009461299,0.001035196,0.000729543,0.0001634372,0.0002745631,0.0001536897,0.005842237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2710004,"threshold_uncertainty_score":0.999645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1709569853040932,"score_gpt":0.453415298759056,"score_spread":0.2824583134549628,"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."}}