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Record W3010320922 · doi:10.7759/cureus.7226

Pituitary Metastasis of Pulmonary Large Cell Neuroendocrine Carcinoma: A Case Report

2020· article· en· W3010320922 on OpenAlexaff
Hsin‐pei Hu, Arpita Sengupta, David Bowes

Bibliographic record

VenueCureus · 2020
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsQueen Elizabeth II Health Sciences CentreWestern UniversityDalhousie University
Fundersnot available
KeywordsMedicinePituitary glandPituitary adenomaMetastasisDiabetes insipidusLungPathologyLesionPathologicalBrain metastasisRadiologyCarcinomaAdenomaInternal medicineCancerHormone

Abstract

fetched live from OpenAlex

The pituitary gland is an uncommon site of tumor metastasis in the brain, comprising only 1% of all intracranial metastasis. Large cell neuroendocrine carcinoma (LCNEC) is similarly rare, accounting for only 3% of all lung malignancies in adults. We describe a case of LCNEC of lung origin that metastasized to the pituitary gland. The pituitary lesion was found during the workup for a metastatic LCNEC of lung origin in the ovary. Initially thought to be a pituitary adenoma, interval growth of the lesion during imaging follow-up raised clinical suspicion of a second metastatic site. The patient underwent endoscopic resection and pathological examination confirmed the pituitary lesion to be from the lung primary. Post-operatively, the patient developed signs and symptoms of diabetes insipidus that was adequately treated with DDAVP. The patient underwent postoperative radiotherapy one month after the surgery and a repeat MRI at the 12-month follow-up demonstrates no progression of the pituitary lesion.

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)0.003
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 score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0030.002

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 head0.267
Teacher spread0.240 · 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
Published2020
Admission routes1
Has abstractyes

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