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Record W3046947055 · doi:10.1155/2020/1543129

Ovarian Cancer Metastasis to the Larynx: A Case Report and Review of the Literature

2020· article· en· W3046947055 on OpenAlexaff
Chad Purcell, Ayham Al Afif, Martin Bullock, Martin Corsten

Bibliographic record

VenueCase Reports in Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsHealth Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineLarynxOvarian cancerSerous fluidMetastasisOvarian carcinomaHypopharyngeal cancerDysphagiaCarboplatinRadiologyBiopsySurgeryChemotherapyCancerPathologyRadiation therapyInternal medicineCisplatin

Abstract

fetched live from OpenAlex

Laryngeal secondary malignancies are rare, and most spread locoregionally from hypopharyngeal or thyroid primaries. Metastasis of ovarian carcinoma to the larynx is extremely rare. A 65-year-old woman with a history of high grade serous ovarian carcinoma was undergoing carboplatin chemotherapy for recurrence. She presented with progressive dysphagia and hoarseness; a computer tomography (CT) scan demonstrated bilateral necrotic lymphadenopathy and hypopharyngeal fullness. A hypopharyngeal mass was confirmed on examination, and operative biopsy identified it as high-grade serous ovarian. To our knowledge, this report describes the second immunohistochemically proven metastatic ovarian cancer detected in the larynx in the world literature.

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 score0.006
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
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 head0.040
GPT teacher head0.316
Teacher spread0.276 · 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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