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Record W2995417115 · doi:10.1111/his.14044

Update on the pathology, genetics and somatic landscape of sebaceous tumours

2019· review· en· W2995417115 on OpenAlexaff
Ingrid Ferreira, Katharina Wiedemeyer, Pieter Demetter, David J. Adams, Mark J. Arends, Thomas Brenn

Bibliographic record

VenueHistopathology · 2019
Typereview
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsUniversity of Calgary
FundersCancer Research UK
KeywordsSebaceous carcinomaLynch syndromeMolecular pathologyPathologyMedicineDifferential diagnosisColorectal cancerCarcinomaCancerBiologyDNA mismatch repairInternal medicineGeneticsGene

Abstract

fetched live from OpenAlex

Cutaneous sebaceous neoplasms show a predilection for the head and neck area of adults and include tumours with benign behaviour, sebaceous adenoma and sebaceoma, and sebaceous carcinoma with potential for an aggressive disease course at the malignant end of the spectrum. The majority of tumours are solitary and sporadic, but a subset of tumours may be associated with Lynch syndrome, also known as hereditary non-polyposis colon cancer (HNPCC) and previously referred to as Muir-Torre syndrome (now known to be part of Lynch syndrome). This review provides an overview of the clinical and histological features of cutaneous sebaceous neoplasia with an emphasis on differentiating features and differential diagnosis. It also offers insights into the recently described molecular pathways involved in the development of sebaceous tumours and their association with Lynch syndrome.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.320
Teacher spread0.265 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations40
Published2019
Admission routes1
Has abstractyes

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