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Record W1525875364 · doi:10.1002/9781118607152.ch11

Primary Tumors of the Central Nervous System

2013· other· en· W1525875364 on OpenAlexaff
Caroline Chung, Eric L. Chang

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineRadiation therapyRadiosurgeryRadioimmunotherapyCentral nervous systemChemotherapyAdjuvantStereotactic radiation therapyOncologyRadiologyInternal medicineAntibody

Abstract

fetched live from OpenAlex

Central nervous system tumors are commonly associated with profound and worrisome symptoms. Radiotherapy plays an important role in the care of most patients who are diagnosed with primary central nervous system tumors. In patients who have recurrent tumor following prior surgery and radiotherapy, with or without chemotherapy, various palliative approaches, including re-irradiation, are being explored to effectively control tumor and maximize quality of life while minimizing toxicity from retreatment. Different radiation delivery techniques have been evaluated including fractionated 3D-conformal, intensity modulated radiation therapy (IMRT), radiosurgery (SRS), and hypofractionated stereotactic radiation therapy (hFSRT). The chapter includes acute and late side effects of radiotherapy, adjuvant treatment modalities, and radioimmunotherapy (RIT) that aims to utilize radioactive isotopes coupled to antibodies in order to increase tumor-specific cell kill.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0240.012

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 head0.007
GPT teacher head0.201
Teacher spread0.195 · 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 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

Citations7
Published2013
Admission routes1
Has abstractyes

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