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Record W2026913456 · doi:10.1179/acb.2009.036

RECOMMENDATIONS FOR RESEARCH FROM THE INTERNATIONAL CONFERENCE OF EXPERTS ON INTRA-ABDOMINAL HYPERTENSION AND ABDOMINAL COMPARTMENT SYNDROME

2009· article· en· W2026913456 on OpenAlexaff
Jan J. De Waele, Michael L. Cheatham, Manu L. N. G. Malbrain, Andrew W. Kirkpatrick, Michael Sugrue, Zsolt J. Balogh, Rao R. Ivatury, Bart De Keulenaer, Edward J. Kimball

Bibliographic record

VenueActa Clinica Belgica · 2009
Typearticle
Languageen
FieldMedicine
TopicAbdominal Surgery and Complications
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsMedicineAbdominal compartment syndromeMultidisciplinary approachBlueprintIntensive care medicineConsensus conferencePsychological interventionSurgeryAbdomenInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: Intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) have been increasingly recognized in the critically ill over the past decade, and the number of published studies has exploded in recent years. Interpretation of the results and comparison of these studies is difficult, because of incomplete and inconsistent reporting of data and statistics. DESIGN: An international consensus group of multidisciplinary specialists convened at the third World Congress on Abdominal Compartment Syndrome to develop recommendations for research related to the diagnosis and management of IAH and ACS. METHODS: Prior to the conference the authors developed a blueprint for consensus definitions and treatment guidelines which were refined both during and after the conference. RESULTS: Three major types of studies were identified (measurement techniques, epidemiology, and interventions), each with different needs regarding methodology, reporting of data and statistical analysis. CONCLUSIONS: These recommendations are proposed to guide clinical research in the field of IAH and ACS.

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)0.247
metaresearch head score (Gemma)0.402
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.247
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2470.402
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0090.016
Bibliometrics0.0180.019
Science and technology studies0.0060.006
Scholarly communication0.0170.017
Open science0.0200.011
Research integrity0.0480.037
Insufficient payload (model declined to judge)0.0240.023

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 head0.423
GPT teacher head0.460
Teacher spread0.038 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations70
Published2009
Admission routes1
Has abstractyes

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