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Record W1493119983 · doi:10.1002/pbc.24851

Stratification of treatment intensity in relapsed pediatric Hodgkin lymphoma

2013· review· en· W1493119983 on OpenAlexaff
Paul Harker‐Murray, Richard A. Drachtman, David Hodgson, Allen R. Chauvenet, Kara M. Kelly, Peter D. Cole

Bibliographic record

VenuePediatric Blood & Cancer · 2013
Typereview
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineLymphomaOncologyHodgkin lymphomaChemotherapyRisk stratificationRegimenRefractory (planetary science)Hematopoietic stem cell transplantationInternal medicineRadiation therapyTransplantation

Abstract

fetched live from OpenAlex

Risk-adapted, response-based therapies for pediatric Hodgkin lymphoma have resulted in 5-year survival exceeding 90%. Although high-dose chemotherapy and autologous hematopoietic stem cell transplantation (AHSCT) are considered standard for most patients with relapsed or refractory Hodgkin lymphoma, a subset of children with low risk relapse do not require AHSCT for cure. Currently there are no widely accepted criteria defining who should receive standard dose chemotherapy and/or radiotherapy, nor is there a standardized treatment regimen. We propose a risk-stratified, response-based algorithm for children with relapsed or refractory Hodgkin lymphoma that is based on a critical appraisal of published outcomes and prognostic factors.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.889
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.053
GPT teacher head0.334
Teacher spread0.281 · 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 designOther design
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

Citations47
Published2013
Admission routes1
Has abstractyes

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