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Record W4294908193 · doi:10.1080/10428194.2022.2109157

Development of a distributed international patient data registry for hairy cell leukemia

2022· article· en· W4294908193 on OpenAlexaff
Leslie A. Andritsos, Mirela Anghelina, Jasmine Neal, James S. Blachly, Puneet Mathur, Omkar Lele, Claire Dearden, Sunil Iyengar, Matt Cross, Clive S. Zent, Kerry A. Rogers, Narendranath Epperla, Gerard Lozanski, Christopher C. Oakes, Eric H. Kraut, Amy S. Ruppert, Qiuhong Zhao, Seema A. Bhat, Francesco Forconi, Versha Banerji, Sasanka M. Handunnetti, Constantine S. Tam, John F. Seymour, Monica Else, Robert J. Kreitman, Alan Saven, Timothy G. Call, Sameer A. Parikh, Farhad Ravandi, James B. Johnston, Enrico Tiacci, Xavier Troussard, Martin S. Tallman, Sascha Dietrich, Tamar Tadmor, Alessandro Gozzetti, Pier Luigi Zinzani, Tadeusz Robak, Graeme Quest, Judit Demeter, Soledad Fernández, Michael R. Grever

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2022
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsKingston Health Sciences CentreQueen's UniversityUniversity of ManitobaResearch Institute in Oncology and Hematology
FundersNational Center for Advancing Translational SciencesNational Cancer InstituteNational Institutes of HealthCancer Research UKHairy Cell Leukemia Foundation
KeywordsHairy cell leukemiaExcellenceMedicineDisease registryLeukemiaDiseasePathologyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

Hairy cell leukemia (HCL) is a rare lymphoproliferative disorder, comprising only 2% of all leukemias. The Hairy Cell Leukemia Foundation (HCLF) has developed a patient data registry to enable investigators to better study the clinical features, treatment outcomes, and complications of patients with HCL. This system utilizes a centralized registry architecture. Patients are enrolled at HCL Centers of Excellence (COE) or via a web-based portal. All data are de-identified, which reduces regulatory burden and increases opportunities for data access and re-use. To date, 579 patients have been enrolled in the registry. Efforts are underway to engage additional COE's to expand access to patients across the globe. This international PDR will enable researchers to study outcomes in HCL in ways not previously possible due to the rarity of the disease and will serve as a platform for future prospective research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.286
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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