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Record W2011262511 · doi:10.3791/52106

Murine Ileocolic Bowel Resection with Primary Anastomosis

2014· article· en· W2011262511 on OpenAlexafffund
Troy Perry, Anna Borowiec, Bryan J. Dicken, Richard N. Fedorak, Karen Madsen

Bibliographic record

VenueJournal of Visualized Experiments · 2014
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates
KeywordsAnastomosisMedicineResectionBowel resectionCrohn's diseaseDiseaseGastrointestinal tractInflammatory bowel diseaseColorectal cancerLeakSurgeryCancerInternal medicine

Abstract

fetched live from OpenAlex

Intestinal resections are frequently required for treatment of diseases involving the gastrointestinal tract, with Crohn's disease and colon cancer being two common examples. Despite the frequency of these procedures, a significant knowledge gap remains in describing the inherent effects of intestinal resection on host physiology and disease pathophysiology. This article provides detailed instructions for an ileocolic resection with primary end-to-end anastomosis in mice, as well as essential aspects of peri-operative care to maximize post-operative success. When followed closely, this procedure yields a 95% long-term survival rate, no failure to thrive, and minimizes post-operative complications of bowel obstruction and anastomotic leak. The technical challenges of performing the procedure in mice are a barrier to its wide spread use in research. The skills described in this article can be acquired without previous surgical experience. Once mastered, the murine ileocolic resection procedure will provide a reproducible tool for studying the effects of intestinal resection in models of human disease.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.539

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 head0.025
GPT teacher head0.405
Teacher spread0.380 · 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 designBench or experimental
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
Published2014
Admission routes2
Has abstractyes

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