MétaCan
Menu
Back to cohort

Unilateral Nephrectomy in 10 Cattle

2011· article· en· W2114571411 on OpenAlexaff
Susan R. Vogel, André Desrochers, Marie Babkine, Pierre‐Yves Mulon, Sylvain Nichols

Bibliographic record

VenueVeterinary Surgery · 2011
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
Fundersnot available
KeywordsMedicineNephrectomyCreatinineBlood urea nitrogenHerdSurgeryMedical recordKidneyInternal medicineVeterinary medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe clinical and imaging findings, treatment, and long-term outcome of cattle undergoing unilateral nephrectomy. STUDY DESIGN: Case series. ANIMALS: Cattle (n=10). METHODS: Medical records (January 1991-August 2008) of cattle that had unilateral nephrectomy were reviewed. Follow-up data were obtained by owner telephone interview. RESULTS: Nephrectomy was performed without surgical complications. Transient increases in blood urea nitrogen and creatinine concentrations occurred after surgery and then returned to, or below, presurgical values in 9 cattle. Nine cows were discharged and 7 rejoined their respective herd as productive animals without long-term complications. CONCLUSIONS: Ultrasonography was the most useful imaging tool for presurgical diagnosis. Based on our follow-up data, unilateral nephrectomy resulted in few serious short-term or long-term complications, and cattle undergoing this procedure are capable of satisfactory growth, reproduction, and milk production after surgery.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.248
GPT teacher head0.325
Teacher spread0.077 · 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 designCase report
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

Citations11
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueVeterinary SurgerySame topicVeterinary Medicine and SurgeryFrench-language works237,207