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Record W2514921213 · doi:10.1111/vsu.12532

Outcome Following Partial Unilateral Hysterectomy by Standing Flank Approach in Dairy Cattle

2016· article· en· W2514921213 on OpenAlexaff
Emma Marchionatti, Sylvain Nichols, Marie Babkine, Hélène Lardé, Réjean Lefebvre, André Desrochers

Bibliographic record

VenueVeterinary Surgery · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineHysterectomySurgeryFlank

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the clinical findings, surgical treatment, and long-term outcome of dairy cattle undergoing partial hysterectomy with or without unilateral ovariectomy. STUDY DESIGN: Retrospective case series. ANIMALS: Dairy cattle (n = 7). METHODS: Medical records (June 2007-June 2014) of dairy cattle that had partial hysterectomy with or without ipsilateral ovariectomy were reviewed. Follow-up data were obtained by telephone interviews with owners and referring veterinarians between 6 months and 7 years following discharge. RESULTS: Seven dairy cattle met the inclusion criteria. Diagnoses made intra- or postoperatively were ovarian abscess with multiorgan adhesions (4 cows), segmental aplasia of the uterus (2 cows), and uterine lymphosarcoma (1 cow). Partial hysterectomy with or without unilateral ovariectomy was performed without surgical complications by standing flank approach. All cows were successfully discharged from the hospital (short-term prognosis). Five cows became pregnant, and 4 delivered live calves and had a satisfactory productive life without long-term complications. CONCLUSION: Partial hysterectomy by standing flank approach should be considered as a viable treatment option for unilateral ovarian or uterine problems in dairy cattle. Cattle undergoing partial hysterectomy with or without ipsilateral ovariectomy are capable of satisfactory reproduction and milk production after surgery with no short- or long-term complications.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.074
GPT teacher head0.271
Teacher spread0.197 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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