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Record W3183167527 · doi:10.3390/biomedicines9080867

Post-Operative Adhesions: A Comprehensive Review of Mechanisms

2021· review· en· W3183167527 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiomedicines · 2021
Typereview
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineIntensive care medicineEtiologyMechanism (biology)Clinical trialAdhesionPsychological interventionSurgeryBioinformaticsPathologyBiology

Abstract

fetched live from OpenAlex

Post-surgical adhesions are common in almost all surgical areas and are associated with significant rates of morbidity, mortality, and increased healthcare costs, especially when a patient requires repeat operative interventions. Many groups have studied the mechanisms driving post-surgical adhesion formation. Despite continued advancements, we are yet to identify a prevailing mechanism. It is highly likely that post-operative adhesions have a multifactorial etiology. This complex pathophysiology, coupled with our incomplete understanding of the underlying pathways, has resulted in therapeutic options that have failed to demonstrate safety and efficacy on a consistent basis. The translation of findings from basic and preclinical research into robust clinical trials has also remained elusive. Herein, we present and contextualize the latest findings surrounding mechanisms that have been implicated in post-surgical adhesion formation.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.421
Teacher spread0.328 · 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