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Record W4297770853 · doi:10.3747/co.v16i1.308

Brain Metastasis from an Unknown Primary, or Primary Brain Tumour? A Diagnostic Dilemma

2009· article· en· W4297770853 on OpenAlexaffvenue
Sarah Campos, Phil Davey, Amanda Hird, Bryn Pressnail, J. R. Bilbao, RI Aviv, Sean Symons, Farhad Pirouzmand, Emily Sinclair, Shaelyn Culleton, E. DeSa, Philiz Goh, E CHOW

Bibliographic record

VenueCurrent Oncology · 2009
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsRoyal Victoria Regional Health CentreResponse Biomedical (Canada)Health Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBrain metastasisRadiation therapyMetastasisBrain tumorPrimary tumorChemotherapyCancerRadiosurgeryBrain cancerOncologyRadiologyPathologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Brain metastasis is increasingly common, affecting 20%–40% of cancer patients. After diagnosis, survival is usually limited to months in these patients. Treatment for brain metastasis includes whole-brain radiation therapy, surgical resection, or both. These treatments aim to slow progression of disease and to improve or maintain neurologic function and quality of life. Although less common, primary brain tumours produce symptoms that are similar to those of brain metastasis. Glioblastoma, the most common malignant tumour of the brain, has a median survival of less than 12 months. Patients are often treated with surgical resection followed by radical radiation therapy and chemotherapy. Here, we present 2 separate cases of lesions in the brain radiologically compatible with brain metastasis. In both cases, no primary cancer site had been established, and neurosurgical intervention was sought to obtain a pathologic diagnosis. Both cases were pathologically confirmed as glioblastoma. These cases demonstrate the importance of differentiation between brain metastases and primary brain tumours to ensure that the appropriate management strategy is implemented.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.088
GPT teacher head0.405
Teacher spread0.316 · 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.

Study designOther design
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

Citations59
Published2009
Admission routes2
Has abstractyes

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