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Record W1489985276 · doi:10.1017/cbo9780511544712.036

Acute respiratory failure

2006· book-chapter· en· W1489985276 on OpenAlexaff
J. E. E. Van Aerde, Michael Narvey

Bibliographic record

VenueCambridge University Press eBooks · 2006
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsStollery Children's Hospital
Fundersnot available
KeywordsRespiratory failureMedicineRespiratory systemAcute respiratory failureIntensive care medicineComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Feeding a patient with respiratory failure is more complicated in a neonatal than in an adult intensive care setting. For adults the goal is to maintain an acceptable energy balance without imposing extra metabolic and respiratory stress on the organism. In newborn infants, the caloric cost for growth has to be added to the energy balance which means that additional respiratory demands will be imposed on the neonate, because the growth process itself produces carbon dioxide and consumes oxygen. Nutritional status affects the respiratory system directly by providing energy for the respiratory muscles and development of lung structure and function; indirectly, the level of energy intake (EI) and the dietary macronutrient composition modify the metabolic demands and affect the respiratory system by modifying central ventilatory drive and the respiratory gaseous exchange. This chapter describes the effect of nutrition on the development and function of the respiratory system in newborns. The first portion describes the interactions between nutrition and structural, biochemical, and functional changes in the lung. The second part addresses metabolic needs of infants with acute respiratory distress and describes the effects of EI and/or diet composition on respiratory gas exchange and energy metabolism in intravenously fed neonates. Nutrition, metabolism, and the respiratory system Lung development and morphology The preterm infant with a birth weight of 1000 g has an expendable nonprotein energy reserve of less than 200 kcal, with 1%–2% of the body weight as fat and less than 1% as glycogen.

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)0.000
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0300.009

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 head0.012
GPT teacher head0.191
Teacher spread0.180 · 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
GenreReview

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
Published2006
Admission routes1
Has abstractyes

Explore more

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