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Record W3001310773 · doi:10.5326/jaaha-ms-6923

Single-Port Laparoscopic Treatment and Outcome of Dogs with Ovarian Remnant Syndrome: 13 Cases (2010–2018)

2020· article· en· W3001310773 on OpenAlexaff
Aaron Percival, Ameet Singh, Cathy Gartley, Ingrid M. Balsa, J. Brad Case, Philipp D. Mayhew, Michelle L. Oblak, Brigitte A. Brisson, Jeffrey J. Runge, Alexander Valverde, Robert A. Linden, Matthieu Gatineau

Bibliographic record

VenueJournal of the American Animal Hospital Association · 2020
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsUniversity of GuelphCanadian Veterinary Medical Association
Fundersnot available
KeywordsMedicinePort (circuit theory)LaparoscopySurgeryGynecologyGeneral surgery

Abstract

fetched live from OpenAlex

ABSTRACT Ovarian remnant syndrome (ORS) is a condition resulting from incomplete removal of ovarian tissue during ovariectomy and/or ovariohysterectomy. Single-port laparoscopy (SPL) is an alternative to ventral midline laparotomy for treatment of ORS. Medical records of 13 client-owned female dogs who underwent SPL for the treatment of ORS were retrospectively reviewed to evaluate surgical technique and outcome. Dogs who had undergone a previous attempt at open ovariectomy or ovariohysterectomy were included. Major intraoperative complications did not occur and conversion to open laparotomy was not required. In 1 dog, an SPL + 1 technique was used, in which an additional port was placed cranial to the single-port device to aid in dissection and tissue manipulation. Median surgical time was 45 min (range, 30–90 min). Clinical signs related to estrus had resolved in 11 of 13 dogs with a median follow-up time of 18 mo. Two of 13 dogs were lost to follow-up at 3 mo postoperatively; however, signs of estrus had resolved at time of last follow-up. SPL treatment for ORS was feasible and successful in this cohort of dogs. Reduced surgical time was found in this study compared with previous reports investigating multiple-port laparoscopic treatment of ORS.

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 score0.045
Threshold uncertainty score0.408

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 studies0.0000.000
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 head0.050
GPT teacher head0.286
Teacher spread0.236 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

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