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Record W2981723359

Single incision laparoscopic-assisted ovariohysterectomy for an ovarian tumor in a dog.

2017· article· en· W2981723359 on OpenAlexaff
Daniel J. Lopez, Ameet Singh, Tanya Wright, Cathy Gartley, Meagan Walker

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineSurgeryInsufflationLaparoscopyLaparoscopic surgery
DOInot available

Abstract

fetched live from OpenAlex

This report describes a single-incision, laparoscopic-assisted ovariohysterectomy in a 6-year-old, intact female Keeshond dog for the staging and treatment of a left-sided ovarian tumor. Abdominal access was obtained using a modified-Hasson technique allowing for placement of a multi-channel, single incision laparoscopic surgery port. Following carbon dioxide insufflation, superficial laparoscopic exploration of the abdominal cavity was performed and then both ovarian pedicles were sealed and divided using a vessel-sealing device. Laparoscopic-assisted ovariohysterectomy was performed with the aid of a wound retractor for exteriorization of the mass. There were no perioperative complications and the patient was discharged 1 day after surgery. Histopathology of the mass revealed an ovarian teratoma. Telephone follow-up 608 days after surgery revealed a good clinical outcome. Single-incision, laparoscopic-assisted ovariohysterectomy is technically feasible for the treatment of selected ovarian tumors in the dog.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.850
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.199
GPT teacher head0.355
Teacher spread0.156 · 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
Published2017
Admission routes1
Has abstractyes

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