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Co-Bedding Twins

2007· article· en· W2080755049 on OpenAlexaff
Kathryn Hayward, Marsha Campbell‐Yeo, Sheri Price, Della Morrison, Robin K. Whyte, Heather Cake, Jocelyn Vine

Bibliographic record

VenueNursing Research · 2007
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsDalhousie University
Fundersnot available
KeywordsProtocol (science)Data collectionMedicinePilot trialClinical trialResearch designPsychologyRandomized controlled trialAlternative medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Co-bedding, a developmental care practice for twins and multiples, has been theorized as a strategy to decrease the adverse neurodevelopmental effects that may be associated with hospitalization. OBJECTIVE: The aim of this study was to determine the feasibility of study design, methods, and the measurement of desired outcomes for the development of a larger multicentered study. RESULTS: Study findings were used to estimate effect size, determine staff and bedside care organization, evaluate feasibility of data collection measures, and identify issues related to recruitment and follow-up. Results were incorporated in the development of a larger multicentered trial grant proposal. DISCUSSION: Pilot studies can play an important role in the development of a competitive grant proposal and efficient conduct of a research trial. Pilot studies strengthen a proposal by providing essential baseline information. A general overview of the purpose of pilot studies is provided here, along with a description of the process of using findings from a pilot study to inform the development of a larger multisite trial. Findings from this pilot study examining the effects of co-bedding on twins and their parents are used to revise the research protocol for a larger multisite trial. These changes, which lead to improvement to the protocol, and the rational for these changes are highlighted.

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)0.003
metaresearch head score (Gemma)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.103
GPT teacher head0.481
Teacher spread0.379 · 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

Citations13
Published2007
Admission routes1
Has abstractyes

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