MétaCan
Menu
Back to cohort
Record W134344556

Neoplasia of the skin

2010· article· en· W134344556 on OpenAlex
Mirinda Van Schoor

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUpSpace Institutional Repository (University of Pretoria) · 2010
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

PHOTOS 1-5: Neoplasia of the skin and subcutaneous tissues are the most common tumours affecting dogs and there are several different types of neoplasia found in skin. Skin tumours are usually classified histologically as there are so many cutaneous structures that could be involved. Tumours are classified according to the tissue of origin and the level of malignancy. Mast cell tumours are the most common type of cutaneous tumour found in dogs. Schnauzers, Boston terriers and Labrador retrievers are some of the breeds that are predisposed to mast cell tumours. Cutaneous mast cell tumours arise from mast cells in the dermis and subcutaneous tissues. These tumours are often infiltrative and metastasize easily to bone marrow and other organs. Undifferentiated mast cell tumours are big, rapidly growing, ulcerated lesions. Hair loss and erythema are common. Mast cell tumours are diagnosed via fine needle aspiration cytology. Rowmanovsky and rapid haematologic type stains are used. Treatment is via surgical excision, radiation therapy or external beam radiotherapy. Poorly differentiated, metastatic mast cell tumours are fatal if there is not effective post surgical treatment. PHOTO 6: Eyelid neoplasms are common in older dogs and are usually benign. Eyelid masses can be resected but the eyelid structure must be restored after excision to maintain long-term ocular surface health. If the structure of the eyelid is damaged it may cause corneal exposure, irritation and ulceration. The most common eyelid neoplasms are sebaceous gland tumours, papillomas and melanomas. Papillomas are more common in younger dogs. Ocular papillomas may have papovavirus aetiology. Eyelid masses that are rapidly growing and ulcerated or are associated with corneal irritation should be resected as soon as possible. Histologically malignant eyelid tumours rarely metastasize and most eyelid tumours are histologically benign. Prognosis for most eyelid tumours is good as metastasis is rare and recurrence rates are low.

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.

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 score0.244
Threshold uncertainty score0.314

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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