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Record W2153755912 · doi:10.1139/cjpp-2014-0387

Perinatal oxygen in the developing lung

2014· review· en· W2153755912 on OpenAlexvenueno aff
Elizabeth R. Vogel, Rodney D. Britt, Mari Charisse Trinidad, Arij Faksh, Richard J. Martin, Peter M. MacFarlane, Christina M. Pabelick, Y. S. Prakash

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2014
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthMayo Clinic
KeywordsBronchopulmonary dysplasiaMedicineHypoxia (environmental)LungOxygen toxicityIntensive care medicinePopulationPremature birthDiseaseLung diseaseAsthmaNeonatal intensive care unitPediatricsPregnancyGestational ageInternal medicineEnvironmental healthOxygen

Abstract

fetched live from OpenAlex

Lung diseases, such as bronchopulmonary dysplasia (BPD), wheezing, and asthma, remain significant causes of morbidity and mortality in the pediatric population, particularly in the setting of premature birth. Pulmonary outcomes in these infants are highly influenced by perinatal exposures including prenatal inflammation, postnatal intensive care unit interventions, and environmental agents. Here, there is strong evidence that perinatal supplemental oxygen administration has significant effects on pulmonary development and health. This is of particular importance in the preterm lung, where premature exposure to room air represents a hyperoxic insult that may cause harm to a lung primed to develop in a hypoxic environment. Preterm infants are also subject to increased episodes of hypoxia, which may also result in pulmonary damage and disease. Here, we summarize the current understanding of the effects of oxygen on the developing lung and how low vs. high oxygen may predispose to pulmonary disease that may extend even into adulthood. Better understanding of the underlying mechanisms will help lead to improved care and outcomes in this vulnerable population.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.086
GPT teacher head0.448
Teacher spread0.362 · 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 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

Citations64
Published2014
Admission routes1
Has abstractyes

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