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Record W4408907078 · doi:10.37464/2025.421.2200

Newborn pain: Evidence and implementation

2025· article· en· W4408907078 on OpenAlexaff
Denise Harrison, Mariana Bueno

Bibliographic record

VenueAustralian journal of advanced nursing · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProject commissioningPublishingMedicineNursingPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abundant evidence exists regarding analgesic effects of breastfeeding, skin-to-skin holding and small volumes of sweet solutions before and during commonly performed needle procedures in sick and healthy newborn infants and young infants. Synthesised evidence, clinical practice guidelines, policies and co-produced staff and parent-targeted online resources exist summarising and showing the effectiveness of these strategies in practice. However, uptake of the evidence has been slow in the diverse settings where sick and healthy infants are cared for. Implementing these strategies is the responsibility of organisations where painful procedures take place, professional associations, leaders and individuals involved in caring for newborns and their families.

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)0.108
metaresearch head score (Gemma)0.412
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 score0.108
Threshold uncertainty score0.570

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1080.412
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0080.008
Science and technology studies0.0020.003
Scholarly communication0.0100.007
Open science0.0050.007
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0160.002

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 head0.028
GPT teacher head0.397
Teacher spread0.369 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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