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Record W4282941328 · doi:10.4103/sjopt.sjopt_93_21

Oncocytic lesions of the ocular adnexa

2021· article· en· W4282941328 on OpenAlexaff
John G. Heathcote, Curtis W. Archibald, Alejandra A. Valenzuela

Bibliographic record

VenueSaudi Journal of Ophthalmology · 2021
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsOncocytomaPathologyEosinophilicHistogenesisHistopathologyMedicineAdenomaThyroidCarcinogenesisBiologyImmunohistochemistryCancerEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Oncocytic lesions may be metaplastic, hyperplastic, or neoplastic and occur in a variety of tissues, including those of the ocular adnexa. Oncocytes are enlarged epithelial cells with abundant eosinophilic granules in the cytoplasm, which represent large mitochondria with distorted cristae. The causes of oncocytic lesions remain uncertain, although in some sites such as the lacrimal sac, chronic inflammation may be a factor. Oncocytic neoplasms in all adnexal sites are generally benign (oncocytoma/oncocytic adenoma) and oncocytic adenocarcinomas are uncommon. Research into oncocytic neoplasms, particularly of the kidney and thyroid, has shed some light on the complicated genomic and metabolic changes that are associated with mitochondrial dysfunction in such neoplasms. The major driver event is mutation of mitochondrial DNA-encoding subunits of complex I in the respiratory chain. The subsequent metabolic events may promote tumorigenesis and inhibit malignant transformation. This review discusses the histopathology and histogenesis of two examples of oncocytoma in the ocular adnexa and presents a simplified synopsis of the genomic and metabolic changes that are significant in the pathogenesis of these neoplasms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.034
GPT teacher head0.335
Teacher spread0.301 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2021
Admission routes1
Has abstractyes

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