MétaCan
Menu
← Back to cohort
Record W3160489552 · doi:10.1111/nicc.12627

Core outcome sets in intensive care–what are they and why do we need them? An example for delirium

2021· editorial· en· W3160489552 on OpenAlexaff
Louise Rose, Lisa Burry, Bronagh Blackwood

Bibliographic record

VenueNursing in Critical Care · 2021
Typeeditorial
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsSinai Health SystemUniversity of Toronto
Fundersnot available
KeywordsDeliriumOutcome (game theory)Core (optical fiber)Intensive careIntensive care medicineMedicineComputer scienceMathematics

Abstract

fetched live from OpenAlex

outcome sets in intensive care-what are they and why do we need them?An example for delirium

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)0.212
metaresearch head score (Gemma)0.447
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2120.447
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0090.014
Science and technology studies0.0020.005
Scholarly communication0.0060.010
Open science0.0040.007
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0060.001

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 head0.165
GPT teacher head0.433
Teacher spread0.268 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueNursing in Critical Care→Same topicIntensive Care Unit Cognitive Disorders→French-language works237,207→