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Record W2767736829 · doi:10.28984/drhj.v1i0.16

Improving Communication Given to Parents with Children Born Prematurely

2017· article· en· W2767736829 on OpenAlexaffvenue
Dominique Leroux, Roxanne Bélanger

Bibliographic record

VenueDiversity of Research in Health Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsLaurentian University
Fundersnot available
KeywordsIntervention (counseling)Neonatal intensive care unitMedicinePsychologyDevelopmental psychologyCognitionNursingPediatricsPsychiatry

Abstract

fetched live from OpenAlex

Research has shown that, upon discharge of children born prematurely, parents do not think they have the abilities to care for their child without the staff and technology of the neonatal intensive care unit (NICU) (Jefferies, 2014). After discharge, most preterm babies are followed by a neonatal follow-up program (NFUP). NFUPs provide assessment, monitoring, identification and early intervention for high-risk infants who have been cared for in a NICU (Provincial Council for Maternal and Child Health, 2015). NFUPs serve several purposes, one of which is to provide anticipatory guidance and teaching parents about their child's developmental patterns, thereby fostering parental resilience. Unfortunately, few parents remember the information given to them by health professionals during medical visits (McGrath, 2012). A systematic review will be conducted in order to collect evidence on preterm children development in the domains of language, feeding and cognition, from birth to school age. Several guides will be created in order to better educate and support parents of children born prematurely, during their visits to NFUPs.

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)0.006
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.098
GPT teacher head0.406
Teacher spread0.308 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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