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Record W2067564903 · doi:10.1586/14737140.2014.940325

Stereotactic radiosurgery for multiple brain metastases

2014· review· en· W2067564903 on OpenAlexaff
Tai‐Chung Lam, Arjun Sahgal, Eric L. Chang, Simon S. Lo

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2014
Typereview
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsRadiosurgeryMedicineBrain metastasisMedical physicsOncologyRadiologyInternal medicineRadiation therapyCancerMetastasis

Abstract

fetched live from OpenAlex

Stereotactic radiosurgery (SRS) alone has become one of the treatment options for patients with 1-4 metastases as the detrimental effects of whole brain radiation therapy on neurocognition and quality of life are becoming well known. Multiple randomized control trials also failed to show overall survival benefit of adding whole brain radiation therapy to SRS. However, the role of SRS in multiple brain metastases, especially those with ≥ 4 tumors, remains controversial. The literature is emerging, and the limited evidence suggests that the local control benefit is independent of the number of metastases, and that patients with more than four brain metastases have similar overall survival compared to those with 2-4 tumors. This review aims at summarizing the current evidence of SRS for multiple brain metastases, divided into limited (2-3) and multiple (≥ 4) lesions. It also reviews the technical aspects and cost-effectiveness of SRS.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.829
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.003
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)0.0010.000

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 head0.085
GPT teacher head0.436
Teacher spread0.351 · 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
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

Citations15
Published2014
Admission routes1
Has abstractyes

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