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Record W4386734980 · doi:10.5326/jaaha-ms-7278

Tibial Plateau and Stifle Joint Invasion with a Subcutaneous Mast Cell Tumor

2023· article· en· W4386734980 on OpenAlexaboutno aff
Monique Triglia, Hollie Horton, Melanie Dobromylskyj, Amy Ferreira, W. P. Robinson

Bibliographic record

VenueJournal of the American Animal Hospital Association · 2023
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStifle jointMast (botany)Plateau (mathematics)Mast cellPathologyAnatomyCruciate ligamentImmunology

Abstract

fetched live from OpenAlex

A 4 yr old female neutered Labrador retriever was referred with a history of left hind-limb lameness and an acute, nonpainful, subcutaneous mass on the medial aspect of the left stifle. Stifle radiographs and fine needle aspirates of the soft tissue mass performed by the referring veterinarian confirmed the presence of predominantly highly granulated mast cells, consistent with a mast cell tumor. Computed tomography demonstrated a soft tissue mass centered on the left medial stifle, with associated joint effusion and polyostotic lytic lesions on the tibial plateau and distal patella. Ultrasound-guided aspirates of the liver, spleen, and popliteal lymph nodes were obtained to rule out further metastatic spread. Cytology of the joint fluid demonstrated a low number of well-differentiated mast cells. Surgical and oncological interventions were discussed, and full hind-limb amputation was elected. Histopathological analysis of the submitted tissues after amputation diagnosed a subcutaneous mast cell tumor with neoplastic cell infiltrate extending into sections of joint capsule and synovial membrane. Infiltration to the tibia and distal patella were suspected following the presence of mast cell clusters in both osteolytic lesions. No evidence of metastasis was identified in the popliteal lymph node. Postoperative monitoring of iliac lymph node size using ultrasound did not identify evidence of metastasis 12 mo postoperatively.

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)0.001
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 score0.266
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.017
GPT teacher head0.275
Teacher spread0.258 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

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