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Record W1497286451 · doi:10.1159/000331182

Advances in Radiation Therapy of Brain Metastasis

2012· review· en· W1497286451 on OpenAlexaff
Simon S. Lo, Arjun Sahgal, Lijun Ma, Eric L. Chang

Bibliographic record

VenueProgress in neurological surgery · 2012
Typereview
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRadiation therapyBrain metastasisBrain diseaseSystemic therapyDiseaseCancerMetastasisRadiologyIntensive care medicineOncologyInternal medicineBreast cancer

Abstract

fetched live from OpenAlex

The traditional treatment for brain metastases is to administer whole-brain radiation therapy using two-dimensional techniques. Owing to the short survival duration of patients historically treated, most patients with brain metastases did not survive long enough to manifest neurologic/neuropsychologic complications. With improved systemic therapy, and more aggressive focal treatment options, longer survival times are now becoming observed along with late effects of cancer treatment. Recently, advances in radiation therapy for brain metastases have taken shape in an attempt to improve the therapeutic ratio of improving intracranial disease control while reducing neurotoxicities. This review provides an overview of advances in the radiotherapeutic management of brain metastases.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.121
GPT teacher head0.392
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2012
Admission routes1
Has abstractyes

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