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Record W2102419757 · doi:10.1186/cc13815

Acidosis in the critically ill - balancing risks and benefits to optimize outcome

2014· letter· en· W2102419757 on OpenAlexaff
Gerard F. Curley, John G. Laffey

Bibliographic record

VenueCritical Care · 2014
Typeletter
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineIntensive care medicineHypercapniaCritically illAcidosisMetabolic acidosisCritical illnessHarmLactic acidosisAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Acidosis is associated with poor outcome in critical illness. However, acidosis - both hypercapnic and metabolic - has direct effects that can limit tissue injury induced by many causes. There is also a clear potential for off-target harm with acute exposure (for example, raised intracranial pressure, pulmonary hypertension), and with exposure for prolonged periods (for example, increased risk of infection) or at high doses. Ongoing comprehensive determination of molecular, cellular and physiologic impact across a range of representative pathologies will allow us to understand better the risks and benefits of hypercapnia and acidosis during critical illness.

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)0.001
metaresearch head score (Gemma)0.012
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 score0.019
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0190.021
Insufficient payload (model declined to judge)0.0020.002

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 head0.073
GPT teacher head0.348
Teacher spread0.275 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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