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Regional Neonatal Oral Feeding Protocol

2004· article· en· W2070518870 on OpenAlexaffabout
Shahirose Premji, Deborah McNeil, Jeanne Scotland

Bibliographic record

VenueThe Journal of Perinatal & Neonatal Nursing · 2004
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsFoothills Medical CentreUniversity of Calgary
Fundersnot available
KeywordsNeonatal intensive care unitNursingMedicineWorkforceSkill mixProtocol (science)Neonatal nursingBreastfeedingIntensive careEconomic shortageUnit (ring theory)Health carePsychologyPediatricsIntensive care medicineAlternative medicine

Abstract

fetched live from OpenAlex

The Calgary Health Region Neonatal Oral Feeding Protocol is the culminating work of a broad range of healthcare professionals, including staff nurses, nurse practitioners, nurse educators, nurse managers, dietitians, lactation consultants, clinical nurse specialists, and occupational therapists. The protocol represents a synthesis of research evidence and expert opinion pertaining to the introduction and management of oral milk feedings for high-risk infants in the neonatal intensive care unit. This evidence-based neonatal oral feeding protocol is presented to share knowledge and skill required to create positive feeding experiences while assisting high-risk infants to achieve full oral feedings. Goals of this project include promoting consistent neonatal nursing feeding practices and changing the ethos in relation to feeding interactions between caregiver and infant in the neonatal intensive care unit. This culture change will assist nurses to identify what is unique about their professional practice, which is of particular importance given the skill mix resulting from hospital understaffing and a growing nursing workforce shortage.

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)0.022
metaresearch head score (Gemma)0.037
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: Protocol · Consensus signal: none
Teacher disagreement score0.132
Threshold uncertainty score0.443

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0040.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1320.037

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 head0.023
GPT teacher head0.315
Teacher spread0.292 · 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
GenreProtocol

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

Citations46
Published2004
Admission routes2
Has abstractyes

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