MétaCan
Menu
Back to cohort
Record W4384463907 · doi:10.58931/cht.2022.117

Myeloproliferative neoplasms in 2022

2022· article· en· W4384463907 on OpenAlexaff
Dawn Maze

Bibliographic record

VenueCanadian Hematology Today · 2022
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreOttawa Hospital
Fundersnot available
KeywordsPolycythemia veraEssential thrombocythemiaRuxolitinibMyelofibrosisMyeloid leukemiaMedicineJanus kinase 2OncologyDiseaseJanus kinaseInternal medicineStem cellHaematopoiesisImmunologyMyeloproliferative DisordersMyeloproliferative neoplasmMyeloidCancer researchBone marrowBiologyCytokineReceptor

Abstract

fetched live from OpenAlex

The Philadelphia chromosome(Ph)-negative myeloproliferative neoplasms (MPN) are comprised of a heterogenous group of disorders of myeloid hematopoietic stem cells that include polycythemia vera (PV), essential thrombocythemia (ET), and idiopathic myelofibrosis (MF). MPN are characterized by constitutional and other disease-related symptoms, an increased risk for thrombotic and hemorrhagic events, and a propensity to transform to acute myeloid leukemia (AML). Progress in our understanding of the molecular pathophysiology of MPN has led to improved prognostic tools, and increasingly personal risk-stratification. In PV, there has been renewed interest in interferon (IFN) for its potential to directly target the malignant clone and exert a disease-modifying effect. In MF, the introduction of Janus Kinase (JAK) inhibitors has significantly altered the therapeutic landscape over the past decade. Ongoing development in the area of JAK inhibitor therapy, as well as several novel pathways, holds promise for improved hematologic responses, lessening of overall burden of illness, increased quality of life, and application to a broader cohort of patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0290.006

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 head0.012
GPT teacher head0.250
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Explore more

Same venueCanadian Hematology TodaySame topicMyeloproliferative Neoplasms: Diagnosis and TreatmentFrench-language works237,207