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Record W4403014078 · doi:10.1016/s2352-3026(24)00276-x

Radiation target nomenclature for lymphoma trials: consensus recommendations from the National Clinical Trials Network groups

2024· article· en· W4403014078 on OpenAlexaff
Omran Saifi, Chelsea C. Pinnix, Leslie Ballas, Chris R. Kelsey, Sarah A. Milgrom, Stephanie A. Terezakis, Nicholas Figura, Rahul R. Parikh, J.C. Grecula, Stella Flampouri, Chul S. Ha, Andrea Lo, John P. Plastaras, David Hodgson, Bradford S. Hoppe

Bibliographic record

VenueThe Lancet Haematology · 2024
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreCanadian Centre for Applied Research in Cancer Control
FundersNational Institutes of HealthNational Comprehensive Cancer NetworkNational Cancer InstituteAmerican Association of Physicists in Medicine
KeywordsMedicineClinical trialNomenclatureLymphomaMedical physicsIntensive care medicineInternal medicineTaxonomy (biology)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.458
metaresearch head score (Gemma)0.493
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.542
Threshold uncertainty score0.668

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4580.493
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0200.022
Bibliometrics0.0120.016
Science and technology studies0.0060.009
Scholarly communication0.0240.011
Open science0.0300.011
Research integrity0.0270.052
Insufficient payload (model declined to judge)0.0080.009

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 head0.287
GPT teacher head0.483
Teacher spread0.196 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations11
Published2024
Admission routes1
Has abstractno

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