MétaCan
Menu
Back to cohort
Record W2077106046 · doi:10.1177/0148607111417446

Nutrition in Burns

2011· review· en· W2077106046 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

VenueJournal of Parenteral and Enteral Nutrition · 2011
Typereview
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Institutes of Health
KeywordsWastingMedicineIntensive care medicineCachexiaCatabolismParenteral nutritionStarvationSevere burnHypermetabolismProtein catabolismTotal body surface areaBurn injuryMedical nutrition therapySurgeryInternal medicineMetabolismBiology

Abstract

fetched live from OpenAlex

Aggressive nutrition support is recommended following severe burn injury. Initially, such injury results in a prolonged and persistent hypermetabolic response mediated by a 10- to 20-fold elevation in plasma catecholamines, cortisol, and inflammatory mediators. This response leads to twice-normal metabolic rates, whole-body catabolism, muscle wasting, and severe cachexia. Thus, it is relevant to review the literature on nutrition in burns to adjust/update treatment. Failure to meet the increased substrate requirements may result in impaired wound healing, multiorgan dysfunction, increased susceptibility to infection, and death. Therefore, aggressive nutrition support is essential to ensure adequate burn care, attenuate the hypermetabolic response, optimize wound healing, minimize devastating catabolism, and reduce morbidity and mortality. Here, the authors provide nutrition recommendations gained from prospective trials, retrospective analyses, and expert opinions based on the authors' practices in Galveston, Texas, and Vienna, Austria.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.904
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
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 head0.072
GPT teacher head0.350
Teacher spread0.278 · 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