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Record W2064394897 · doi:10.1186/cc7917

Broadening our perspectives on ICU delirium risk factors

2009· letter· en· W2064394897 on OpenAlexaff
Yoanna Skrobik

Bibliographic record

VenueCritical Care · 2009
Typeletter
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsDeliriumMedicineIntensive care medicineRisk stratificationCognitive impairmentRisk factorEmergency medicineAlcohol consumptionProspective cohort studyCognitionPsychiatryAlcoholInternal medicine

Abstract

fetched live from OpenAlex

ICU delirium is associated with poor patient outcome. Risk factor stratification is essential to the understanding, prevention and treatment of this disorder. Alcohol consumption, smoking and prior cognitive impairment appear strongly correlated with delirium risk. Several potentially modifiable associations deserve prospective study: these include administration of sedatives and opiates; multiple catheters; as well as minimizing physical restraints and enabling visitors.

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)0.015
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.027
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0030.002
Science and technology studies0.0030.008
Scholarly communication0.0070.019
Open science0.0040.007
Research integrity0.0270.039
Insufficient payload (model declined to judge)0.0090.004

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 head0.026
GPT teacher head0.329
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations10
Published2009
Admission routes1
Has abstractyes

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