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Record W105575090 · doi:10.1093/pch/20.2.e10

Time needed to achieve changes in oxygen concentration at the T-Piece resuscitator during respiratory support in preterm infants in the delivery room

2015· article· en· W105575090 on OpenAlexaff
Graeme Follett, Po‐Yin Cheung, Gerhard Pichler, Khalid Aziz, Georg M. Schmölzer

Bibliographic record

VenuePaediatrics & Child Health · 2015
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNeonatal resuscitationResuscitationAnesthesiaMedicineFraction of inspired oxygenOxygen deliveryOxygenVentilation (architecture)Mechanical ventilationChemistryPhysics

Abstract

fetched live from OpenAlex

OBJECTIVE: To measure the time needed to achieve changes in fraction of inspired oxygen concentration (FiO2) from the oxygen blender to the facemask during simulated neonatal resuscitation. METHOD: Two oxygen analyzers were placed at each end of the T-Piece. During simulated ventilation, the duration to achieve the set oxygen concentration at the facemask was measured. This was repeated at different gas flow rates (5 L/min, 8 L/min or 10 L/min) and different FiO2 changes (0.21 to 1.0 to 0.21, with stepwise increases and decreases in 0.05, 0.1 and 0.2 increments). RESULTS: A total of 1134 measurements (378 measurements for each flow) were recorded. Overall, the mean (± SD) time required to achieve FiO2 changes at 5 L/min, 8 L/min and 10 L/min was 36±15 s, 31±14 s and 28±14 s, respectively. CONCLUSION: There was a lag time of approximately 30 s to achieve the FiO2 at the facemask. This delay needs to be considered when making serial adjustments to FiO2 during neonatal resuscitation.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.341
Teacher spread0.296 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2015
Admission routes1
Has abstractyes

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