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Record W2531826088 · doi:10.1097/rlu.0000000000001396

Cerebral Proliferative Angiopathy (CPA)

2016· article· en· W2531826088 on OpenAlexaff
Egesta Lopci, Laura Olivari, Lorenzo Bello, Pierina Navarria, Arturo Chiti

Bibliographic record

VenueClinical Nuclear Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsMedicineCerebellar hemisphereCerebral peduncleAngiopathyCerebral hemisphereLesionBrainstemPathologyMagnetic resonance imagingFrontal lobeRadiologyWhite matterInternal medicine

Abstract

fetched live from OpenAlex

We report the case of a 55-year-old woman with cerebral proliferative angiopathy (CPA). Her medical history included brain surgery for small vascular lesions and suspicion of cerebral malignancy. C methionine PET (C-METH PET) demonstrated a diffusely increased uptake on the right hemisphere. Contrast-enhanced MRI documented a massive lesion with a diffuse "nidus" appearance, involving the right cerebral hemisphere (sparing the inferior frontal gyrus and the anterior frontal lobe), the brainstem, and the middle cerebellar peduncle. Pathology confirmed the diagnosis of CPA and, after radiation treatment, the patient presented with clinical and radiological response.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.999

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)0.0020.001

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 head0.064
GPT teacher head0.373
Teacher spread0.310 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations8
Published2016
Admission routes1
Has abstractyes

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