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Record W2888230221 · doi:10.1111/vde.12683

Combined carbon dioxide laser and cryosurgical ablation of rostral nasal septum squamous cell carcinoma in 10 dogs

2018· article· en· W2888230221 on OpenAlexaboutno aff
Maria K. Ierace, Michael S. Canfield, Jeanine Peters‐Kennedy, Curtis W. Kane

Bibliographic record

VenueVeterinary Dermatology · 2018
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCarbon dioxide laserCryosurgeryAblationBasal cellSurgeryLaser surgeryPathologyInternal medicineLaser

Abstract

fetched live from OpenAlex

BACKGROUND: Squamous cell carcinoma (SCC) is the most commonly reported neoplasm of the nasal planum and treatment is focused on localized disease. Rostral maxillectomy and/or nasal planectomy are considered standard of care for excision of nasal planum SCC; however, the cosmetic outcome of these procedures can be deemed unacceptable by many pet owners. OBJECTIVES: ) laser surgery and cryosurgery as a palliative treatment modality in dogs with nasal SCCs. ANIMALS: Ten client-owned dogs with nasal SCC were included: seven neutered males, two spayed females and one intact male, with a median age of 12.5 years (range 9-15 years). METHODS AND MATERIALS: laser ablation was followed by cryosurgical ablation of the visible tumour, adjacent and subjacent tissue. Three rapid freeze-slow thaw cycles were performed. RESULTS: Eight of 10 dogs were Labrador retrievers. The ages ranged from 9 to 14 years. Overall median survival time was 260 days with two dogs still alive at the time of writing. CONCLUSIONS AND CLINICAL IMPORTANCE: laser and cryosurgical ablation was practical, cost-effective and provided an excellent aesthetic outcome in dogs with SCCs restricted to the nasal septum, while providing acceptable palliation of local 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.029
GPT teacher head0.310
Teacher spread0.281 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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