MétaCan
Menu
Back to cohort
Record W2961557244 · doi:10.1002/ncp.10320

Do We Have Clinical Equipoise (or Uncertainty) About How Much Protein to Provide to Critically Ill Patients?

2019· article· en· W2961557244 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNutrition in Clinical Practice · 2019
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsKingston General HospitalClinical Evaluation Research UnitQueen's University
FundersCanadian Institutes of Health ResearchCumberland PharmaceuticalsGlaxoSmithKline
KeywordsMedicineCritically illGuidelineDosingIntensive care medicineClinical trialClinical equipoiseRandomized controlled trialPharmacologyInternal medicinePathology

Abstract

fetched live from OpenAlex

The current recommendation for protein dose in critically ill patients is 1.2-2.0 g/kg/d. Despite this recommendation, there is significant variation in the amount of protein prescribed and delivered worldwide. We contend clinical equipoise, or a state of genuine uncertainty about 2 (dosing) strategies, exists because guideline-based recommendations for protein dose in critically ill patients are rooted in a weak evidentiary base, leaving the clinician with no good basis for choosing a lower or higher protein dose. We outline evidence for and against high protein dose and introduce a pragmatic, registry-based, multicenter, randomized controlled trial, known as EFFORT, which aims to resolve the high vs low protein dose controversy.

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)0.006
metaresearch head score (Gemma)0.188
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.419
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.188
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.077
GPT teacher head0.441
Teacher spread0.363 · 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