MétaCan
Menu
Back to cohort
Record W4214489424 · doi:10.5935/0103-507x.20210022

Reply to: Complementary of modified NUTRIC score with or without C-reactive protein and subjective global assessment in predicting mortality in critically ill patients

2021· letter· en· W4214489424 on OpenAlexaff
Manoela Lima Oliveira, Daren K. Heyland, Flávia Moraes Silva, Estela Iraci Rabito, Mariane Rosa, Micheli da Silva Tarnowski, Daieni Fernandes, Aline Marcadenti

Bibliographic record

VenueCritical Care Science · 2021
Typeletter
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsCritically illIntensive care medicineMedicineInternal medicine

Abstract

fetched live from OpenAlex

We revised the letter to the Editor about our study with high interest. (1)lease, find below are our comments.Regarding the first comment, we agree that our sample was limited, and our results come from a single-center study; indeed, this was remarked in our manuscript as a limitation.As we stated in Methods, we excluded patients at imminent risk of death, which might have influenced our results.Our team decided to exclude those patients for ethical concerns added to the challenge of collecting a proxy signature on the informed consent form.That

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 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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.077
GPT teacher head0.420
Teacher spread0.342 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCritical Care ScienceSame topicNutrition and Health in AgingFrench-language works237,207