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Record W2143313489 · doi:10.1016/j.ijsu.2011.08.008

Intra-abdominal adhesions: Cellular mechanisms and strategies for prevention

2011· review· en· W2143313489 on OpenAlexafffund
Allison H. Maciver, Michael McCall, A. M. James Shapiro

Bibliographic record

VenueInternational Journal of Surgery · 2011
Typereview
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsUniversity of Alberta Hospital
FundersAlberta Innovates
KeywordsMedicineAdhesionPathogenesisIntensive care medicineDiseaseSurgeryPathology

Abstract

fetched live from OpenAlex

Postoperative intra-abdominal adhesions represent a serious clinical problem. In this review, we have focused on recent progress in the cellular and humoral mechanisms underpinning adhesion formation, and have reviewed strategies that interfere with these pathways as a means to prevent their occurrence. Current and previous English-language literature on the pathogenesis of adhesion formation was identified. As the burden of surgical disease in the world population increases, and the frequency of reoperation increases, prevention of adhesion formation has become a pressing goal in surgical research.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.162
GPT teacher head0.378
Teacher spread0.216 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations161
Published2011
Admission routes2
Has abstractyes

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