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Record W2040744297 · doi:10.5430/jst.v2n1p1

Radiotherapy for brain tumors – New techniques and treatment strategies

2012· article· en· W2040744297 on OpenAlexvenueno aff
Anca‐Ligia Grosu, Franziska Fels

Bibliographic record

VenueJournal of Solid Tumors · 2012
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiation therapyPalpationNuclear medicineRadiation treatment planningRadiologyVolume (thermodynamics)

Abstract

fetched live from OpenAlex

Radiotherapy is generally a local treatment. The radiation oncologist marks image-based the area to be irradiated (targetvolume) as well as areas which should be spared (organs at risk). Three important volumes differ in marking of the targetvolume: gross tumor volume, clinical target volume and planning target volume. Gross tumor volume (GTV) means thevolume where tumor is traceable in CT, MRI, ultrasonic sound, PET or clinical inspection and palpation. Clinical targetvolume (CTV) involves the GTV and the microscopic tumor expansion: peritumoral regions, lymph nodes, perineural orperivascular tumor infiltration, etc. The Planning Target Volume includes the CTV as well as the possible mobility of thetumor and the imprecision in positioning of patients at the linear accelerator. With an exact positioning of the patient at theirradiation device, PTV margin can be considerably reduced. That leads to a reduction of exposure in the healthy tissue andto a dose weighting in the tumor area.

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)0.001
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.026
GPT teacher head0.334
Teacher spread0.308 · 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
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

Citations0
Published2012
Admission routes1
Has abstractyes

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