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Record W2139355832 · doi:10.1186/1746-4358-9-4

Human donor milk for the vulnerable infant: a Canadian perspective

2014· article· en· W2139355832 on OpenAlexaffabout
Julia Panczuk, Sharon Unger, Deborah L. O’Connor, Shoo K. Lee

Bibliographic record

VenueInternational Breastfeeding Journal · 2014
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsMount Sinai HospitalHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBreastfeedingBreast milkMedicinePasteurizationPopulationBreast feedingLow birth weightEnvironmental healthPediatricsPregnancyFood scienceBiology

Abstract

fetched live from OpenAlex

Breast milk is the normal way to feed infants and is accepted worldwide as the optimal first source of nutrition. Though the majority intend to breastfeed, many mothers of sick, hospitalized newborns, particularly those of very low birth weight, are unable to provide a full volume of milk due to numerous physical and emotional barriers to breastfeeding. This vulnerable population of infants may benefit most from receiving breast milk nutrition and thus pasteurized donor milk should be the first consideration for supplementation when there is an inadequate supply of mother's own milk. This commentary will briefly review the history of milk banking in Canada, as well as the best available evidence for donor milk use in the very low birth weight population, including available economic analyses, with a view to advocate for its use in these vulnerable infants.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.314
Teacher spread0.295 · 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.

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

Citations16
Published2014
Admission routes2
Has abstractyes

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