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Record W7127009328

Multi-modal Management of an Oral Amelanotic Malignant Melanoma in a Labrador Retriever

2017· other· en· W7127009328 on OpenAlexaboutno aff
Anastasia Handwerk Breidenbaugh

Bibliographic record

VenueeCommons (Cornell University) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsLabrador RetrieverMelanomaMetastasisLesionAmelanotic melanomaHistologySurgical excisionHead and neck
DOInot available

Abstract

fetched live from OpenAlex

A ten-year-old, intact male, Labrador Retriever was presented to the Cornell University Hospital for Animals' Oncology Service for evaluation of a recurrent oral amelanotic melanoma. This lesion was first noticed by his owners in early March on the right buccal mucosa. The mass had been previously excised by the primary veterinarian. Histology revealed an incompletely excised amelanotic melanoma with a mitotic index of 52 per l0HPF. Staging at CUHA revealed no evidence of metastasis so computed tomographic imaging of the head was performed for surgical planning. A surgical scar revision was performed, along with removal of both mandibular lymph nodes. Samples from the surgical margins were submitted for intraoperative cryosections which revealed clean margins. The mucosa was reconstructed with local mucosa! flaps. At a recheck appointment with the Oncology Service two months following the scar revision, the patient had repeat thoracic radiographs taken and revealed a possible pulmonary nodule, which was later determined to be summation of normal tissue. Three and a half months after the surgical scar revision, the patient presented to the Emergency Service for progressive hind-end weakness and a two day history of inappetance and inability to stand. Imaging revealed evidence of metastasis in the liver and, given a poor prognosis, euthanasia was elected. This report will discuss oral amelanotic melanoma in dogs, common clinical presentations, diagnostics, and potential treatment options for the disease.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.162
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.040
GPT teacher head0.230
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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Same venueeCommons (Cornell University)French-language works237,207