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Record W1923040548 · doi:10.1111/vco.12166

Feline discrete high‐grade gastrointestinal lymphoma treated with surgical resection and adjuvant<scp>CHOP</scp>‐based chemotherapy: retrospective study of 20 cases

2015· article· en· W1923040548 on OpenAlexaff
E. D. Gouldin, Christine Mullin, Michelle A. Morges, Steve J. Mehler, Louis Philippe De Lorimier, C. Elizabeth Oakley, R.E. Risbon, Lorraine F. May, Stacy A. Kahn, Craig A. Clifford

Bibliographic record

VenueVeterinary and Comparative Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsCanadian Veterinary Medical Association
Fundersnot available
KeywordsMedicineCHOPCATSChemotherapyLymphomaSurgeryPeritonitisRetrospective cohort studyVincristineStage (stratigraphy)White blood cellGastrointestinal cancerGastroenterologyInternal medicineCancerColorectal cancer

Abstract

fetched live from OpenAlex

The aim of this retrospective study was to evaluate the outcome of cats treated with surgical intervention for a discrete intermediate-/high-grade gastrointestinal lymphoma prior to CHOP-based chemotherapy. Variables including sex, breed, haematocrit, white blood cell count, serum albumin concentration, clinical stage of disease, gastrointestinal obstruction and peritonitis were assessed for their effect on survival. Twenty cats met the inclusion criteria with three cats still alive at the time of data analysis. The overall median survival time (MST) was 417 days (range: 12-2962 days). The disease-free interval (DFI) was 357 days (range: 0-1585 days) with six cats still deemed in remission prior to death. Only clinical stage had a significant effect on both MST and DFI. Cats with discrete intermediate/high-grade gastrointestinal lymphoma that undergo surgical resection followed by adjuvant CHOP chemotherapy may achieve acceptable overall survival times.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.132
GPT teacher head0.396
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations41
Published2015
Admission routes1
Has abstractyes

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