{"id":"W2514978079","doi":"10.1016/j.humimm.2016.07.072","title":"P007 Utility of autologous crossmatches in resolving unexpected positive flow cytometry crossmatches","year":2016,"lang":"en","type":"article","venue":"Human Immunology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Alberta Health Services","funders":"","keywords":"Flow cytometry; Medicine; Immunology","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":[0.002516003,0.000418717,0.0002497309,0.001041166,0.0004286007,0.0009306968,0.0006321275,0.0008433223,0.006629041],"category_scores_gemma":[0.006823661,0.0002643795,0.0003051318,0.0004610588,0.0005393033,0.0006324358,0.0004342497,0.001129599,0.001884218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003338989,"about_ca_system_score_gemma":0.0004894974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004413091,"about_ca_topic_score_gemma":0.0006831328,"domain_scores_codex":[0.9988995,0.0004897226,0.00006880016,0.0001179717,0.0003038371,0.0001201052],"domain_scores_gemma":[0.9975244,0.001588477,0.0001271799,0.0003073423,0.000333601,0.0001189986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.006168876,0.001051611,0.1563876,0.0007165712,0.0001889134,0.0141925,0.0005464185,0.003137885,0.2544382,0.006690593,0.01255593,0.5439249],"study_design_scores_gemma":[0.0003343758,0.003417247,0.0759722,0.0003561101,0.0005750952,0.1114805,0.0006522857,0.06294116,0.6864501,0.01091931,0.04682127,0.00008038105],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8774543,0.007145411,0.06549136,0.00244704,0.000675254,0.0004085692,0.0003130743,0.00118208,0.04488292],"genre_scores_gemma":[0.9738336,0.001104703,0.02221283,0.0003760269,0.0002009438,0.00004740629,0.0001868821,0.00009001481,0.001947593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006629041,"threshold_uncertainty_score":0.02217638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123837045333878,"score_gpt":0.2642099333462606,"score_spread":0.2518262288128729,"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."}}