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Record W2418507839

A pilot study evaluating laparoscopic closure of the nephrosplenic space using an endoscopic suturing device in standing horses.

2016· article· en· W2418507839 on OpenAlexaff
José L. Bracamonte, Tanya Duke‐Novakovski

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineFasciaFibrous jointLigamentSurgeryHorse
DOInot available

Abstract

fetched live from OpenAlex

This study evaluated the use of an articulating automated suturing device for laparoscopic closure of the nephrosplenic space in standing horses. Closure of the nephrosplenic space was performed in 4 horses using an automated suturing device. Second-look laparoscopy was performed at 5 weeks. A smooth fibrous adhesion formed between the spleen, the perirenal fascia, and the nephrosplenic ligament in 3 of the 4 horses in which the nephrosplenic space was closed using the automated suturing device. In 1 horse, closure of the nephrosplenic space was not possible due to constant breakage of the endoscopic needle. Intra-operative complications encountered with the automated suturing device were tearing of the perirenal fascia, nephrosplenic ligament, and dorsal splenic capsule along with breakage of the needle. The automated suturing device used in this study for laparoscopic closure of the nephrosplenic space resulted in longer surgery times, suffered instrument failures and delivered inadequate suture.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.115
GPT teacher head0.329
Teacher spread0.214 · 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 designNon-randomized trial
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

Citations8
Published2016
Admission routes1
Has abstractyes

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