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Record W4255238151 · doi:10.14740/jnr396w

Brain Radionecrosis: Case Report

2016· article· en· W4255238151 on OpenAlexvenueno aff
Leandro Pelegrini de Almeida, Tobias Ludwig do Nascimento, L. Rogério, Marcelo Reis, Guilherme Finger, Gabriel Frizon Greggianin, Fernanda De Carli, Grégori Manfroi, Eduardo Anzolin, Pasquale Gallo

Bibliographic record

VenueJournal of Neurology Research · 2016
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineComplicationRadiation therapyEtiologyDifferential diagnosisLesionBrain tumorRadiological weaponOsteoradionecrosisSurgeryRadiologyPathology

Abstract

fetched live from OpenAlex

Brain necrosis is a possible complication caused by radiation therapy used in the treatment of head and neck cancer. This complication has variable neurological symptoms according to the site of brain damage, including motor deficits, aphasia, altered consciousness, seizures, and intracranial hypertension and also a variable time for presentation ranging from 3 months to 10 years. Once established, brain injury is irreversible and it is characterized by non-specific radiological image that submits the questions about its etiology: is it secondary to radionecrosis? Tumor progression? Primary tumor? The clinical report here described demonstrates the possibility of such differential diagnosis in a patient with brain lesion as a consequence of radiotherapy for a skin cancer. J Neurol Res. 2016;6(5-6):102-105 doi: https://doi.org/10.14740/jnr396w

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)0.003
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.004
Science and technology studies0.0050.004
Scholarly communication0.0040.004
Open science0.0030.004
Research integrity0.0100.007
Insufficient payload (model declined to judge)0.0050.003

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 head0.121
GPT teacher head0.444
Teacher spread0.323 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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