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Record W3011162850 · doi:10.1093/pch/pxaa002

Are there alternatives to over-the-counter diabetes-care glucose-gels for transitional neonatal hypoglycemia?

2020· article· en· W3011162850 on OpenAlexaffabout
Alfonso Solimano, Horacio Osiovich, Eddie Kwan, Daniel L. Metzger, Rob Everett

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsChildren's & Women's Health Centre of British ColumbiaUniversity of British Columbia
Fundersnot available
KeywordsBreastfeedingHypoglycemiaMedicineNeonatal hypoglycemiaNeonatal intensive care unitPediatricsDiabetes mellitusIntensive care medicineObstetricsPregnancyGestational diabetesGestationEndocrinology

Abstract

fetched live from OpenAlex

Transitional neonatal hypoglycemia is common in at-risk well newborns, requires immediate attention, interferes with breastfeeding, and frequently results in separation of mothers from their babies. Breastfeeding shortly after birth and screening at-risk newborns at 2 hours of age is standard practice in Canada. In the Sugar Babies Trial, a custom-made 40% glucose-gel massaged to the buccal mucosa in at-risk infants decreased intravenous glucose treatment, but not neonatal intensive care unit admission. It increased the rate of full breastfeeding after discharge but experts suggest that additional evidence is needed. Further, commercially available neonatal glucose-gels do not exist, so practitioners around the world have started using diabetes-care products, which do not meet standards for use in newborns. Here, we provide a condensed summary of the topic and of management alternatives.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.287
Teacher spread0.269 · 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
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

Citations1
Published2020
Admission routes2
Has abstractyes

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