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Record W4250043893 · doi:10.1002/9780471420194.tnmm56

Soft tissue

2017· other· en· W4250043893 on OpenAlexaff
Colleen Dickie, Abha A. Gupta, Raphael E. Pollock, Brian O’Sullivan

Bibliographic record

VenueTNM Online · 2017
Typeother
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsRadiation therapyHead and neckMedicineSoft tissueBrachytherapyExternal beam radiotherapySoft tissue sarcomaRadiologyParticle therapySurgery

Abstract

fetched live from OpenAlex

Summary Soft tissue sarcoma is a rare disease requiring multimodality discussion and management. Just over half of these tumours originate in the limbs approximately 40% arise in the retroperitoneum/visceral tissues and torso and the remainder occur in the head and neck region (10%). In general, the treatment approach is surgery with or without the addition of local radiotherapy. Radiation therapy may include particle beam therapy, brachytherapy or external beam techniques, such as conformal radiotherapy and intensity‐modulated radiotherapy (IMRT). Chemotherapy remains controversial and it is usually restricted to established chemoresponsive subtypes and high'risk cases.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.136
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.002

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 head0.034
GPT teacher head0.352
Teacher spread0.318 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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