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Record W196798949

Minimal abdominal adhesions after Sepramesh repair of a parastomal hernia.

2009· article· en· W196798949 on OpenAlexaff
Jim Rose, Shiva Jayaraman, Patrick Colquhoun, Brian M. Taylor

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineAdhesionSurgeryAbdomenSurgical meshHerniaForeign bodyTissue AdhesionAbdominal surgeryAbdominal wallVentral hernia
DOInot available

Abstract

fetched live from OpenAlex

Postoperative adhesions are a major cause of morbidity and mortality in surgical patients. The use of prosthetic meshes in abdominal surgery increases the formation of adhesions by triggering an inflammatory reaction to a foreign body. Although several animal studies have shown that implantation of the composite polypropylene and hyaluronate-carboxymethylcellulose mesh Sepramesh (Genzyme Biosurgery) results in decreased adhesion formation, there is no evidence of this in human studies. To our knowledge, the present case represents the first report of minimal adhesions in an abdomen in which Sepramesh was previously implanted.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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 designCase report
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
Published2009
Admission routes1
Has abstractyes

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