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Record W2070235003 · doi:10.1227/neu.0000000000000654

Letter

2015· letter· en· W2070235003 on OpenAlexaff
Lijun Ma, Arjun Sahgal, David A. Larson

Bibliographic record

VenueNeurosurgery · 2015
Typeletter
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineRadiosurgeryGamma knifeNuclear medicineMedical physicsMedical prescriptionRadiologyRadiation therapy

Abstract

fetched live from OpenAlex

To the Editor: We read with interest the article comparing volumetric modulated arc therapy (VMAT) vs Gamma Knife (GK) radiosurgery treatment planning of multiple brain metastases, in which the authors erroneously conclude “4-arc VMAT produced clinically equivalent conformity, dose falloff, 12 Gy isodose volume, and low isodose spill.”1 Their study applied different prescription isodose volumes for GK plans and VMAT plans, as is apparent in Figure 2, which shows significantly larger prescription isodose volumes for GK plans than for VMAT plans (P < .001). Had the same prescription isodose volumes been used, significantly larger normal tissue doses would have been delivered with VMAT, a result previously demonstrated in multi-institutional benchmark studies.2,3 In short, VMAT delivers faster treatment but with significantly increased normal tissue dose. Disclosures Drs Ma and Sahgal currently serve on the board of International Stereotactic Radiosurgery Society (ISRS). Dr Sahgal also holds research grants with Elekta, AB and has received honoraria for past educational seminars. Otherwise, the authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.054
GPT teacher head0.276
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2015
Admission routes1
Has abstractyes

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