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Record W2264287547 · doi:10.7759/cureus.481

Asymptomatic Evolution and Regression of Temporal Lobe Necrosis After Adjuvant Radiation for Skin Cancer: A Case Report and Review of Literature

2016· article· en· W2264287547 on OpenAlexaff
Rima Pathak, Gaurav Bahl

Bibliographic record

VenueCureus · 2016
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsMedicineAsymptomaticRadiation therapyAdjuvant radiotherapyTemporal lobePathologicalRadiologyModalitiesSurgeryPathology

Abstract

fetched live from OpenAlex

Temporal Lobe Necrosis (TLN) is not an expected complication of adjuvant radiation therapy (RT) for skin cancers and has become uncommon otherwise in daily practice due to improved RT planning and modern delivery techniques. TLN is a great mimic and can be mistaken for disease recurrence, metastasis to the brain, or high grade primary brain tumor. This case report demonstrates the importance of diagnosing the entity, its natural evolution, and dosimetric correlation with published constraints.​ It emphasizes the importance of thorough clinical examination on follow-up and review of previous radiation plan when encountered with challenging differentials. We also provide a review of clinical presentations, imaging modalities, and management options for patients with suspected TLN.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.305
Teacher spread0.294 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations2
Published2016
Admission routes1
Has abstractyes

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