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Record W2621348711 · doi:10.1136/bmj.j2330

Which are the best conservative interventions for lymphoedema after breast cancer surgery?

2017· article· en· W2621348711 on OpenAlexaff
Martijn M. Stuiver, Marieke R. ten Tusscher, Margaret L. McNeely

Bibliographic record

VenueBMJ · 2017
Typearticle
Languageen
FieldMedicine
TopicLymphatic System and Diseases
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineLymphedemaBreast cancerAxillary Lymph Node DissectionLymph nodeDissection (medical)SurgerySentinel lymph nodeIncidence (geometry)CancerGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Lymphoedema is a common complication of breast cancer surgery with or without adjuvant cancer treatments.1 Fluid accumulates because of damage to the lymphatic system, most commonly after axillary lymph node dissection. Box 1 shows factors associated with lymphoedema. Swelling is commonly in the arm but can involve the chest or back; it can result in pain, dysfunction, and disturbance of body image.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.005
Open science0.0010.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0220.005

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 head0.089
GPT teacher head0.389
Teacher spread0.301 · 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 designSystematic review
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

Citations11
Published2017
Admission routes1
Has abstractyes

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