{"id":"W4366607243","doi":"10.1016/j.jtct.2023.04.011","title":"Transplantation Referral Patterns for Patients with Newly Diagnosed Higher-Risk Myelodysplastic Syndromes and Acute Myeloid Leukemia at Academic and Community Sites in the Connect® Myeloid Disease Registry: Potential Barriers to Care","year":2023,"lang":"en","type":"article","venue":"Transplantation and Cellular Therapy","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Sierra Oncology; Incyte; Astex Pharmaceuticals; Astellas Pharma; TG Therapeutics; Karyopharm Therapeutics; Alexion Pharmaceuticals; Sunesis; Teva Pharmaceutical Industries; Bristol-Myers Squibb; AstraZeneca; Agios Pharmaceuticals","keywords":"Medicine; Myeloid leukemia; Transplantation; Myelodysplastic syndromes; Internal medicine; Disease registry; Comorbidity; Referral; Hematopoietic stem cell transplantation; Disease; Cancer registry; Myeloid; Cancer; Family medicine; Bone marrow","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003412543,0.0003098014,0.0003315126,0.0002307978,0.0006630504,0.00006367498,0.0001604748,0.0001603154,0.00001974827],"category_scores_gemma":[0.00003421096,0.0002243834,0.00005166286,0.0002990209,0.0001645763,0.0001592095,0.00001670288,0.0006275337,0.000002722785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001167335,"about_ca_system_score_gemma":0.0001350185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002666032,"about_ca_topic_score_gemma":0.000216135,"domain_scores_codex":[0.9980397,0.00043663,0.0003002125,0.0004126753,0.0004030454,0.0004077574],"domain_scores_gemma":[0.9986153,0.0005312135,0.00008859351,0.0002620807,0.00007110353,0.0004317282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03466969,0.000113109,0.8374869,0.002556768,0.0004268934,0.001074272,0.08413879,0.0002589897,0.03027274,0.00006908196,0.0001609902,0.008771729],"study_design_scores_gemma":[0.01983031,0.001457259,0.9700449,0.0002969987,0.0005385479,0.00007692815,0.004815882,0.0004955122,0.001863433,0.00005267611,0.0001556279,0.0003719109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947673,0.0004010637,0.0006088804,0.0008330377,0.00005205718,0.001958654,0.001292338,0.00007388485,0.00001277186],"genre_scores_gemma":[0.9802508,0.01425343,0.00008727828,0.0004877722,0.00004541612,0.0002602063,0.004497785,0.0000499816,0.00006731108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.132558,"threshold_uncertainty_score":0.9150089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02017834942536912,"score_gpt":0.2748081163798595,"score_spread":0.2546297669544904,"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."}}