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Record W2762776200 · doi:10.11124/jbisrir-2017-003346

Single room versus open-bay design in neonatal intensive care units for improvement in infant outcomes: a systematic review protocol

2017· review· en· W2762776200 on OpenAlexaff
Timothy Disher, Justine Dol, Brianna Hughes, Marsha Campbell‐Yeo

Bibliographic record

VenueThe JBI Database of Systematic Reviews and Implementation Reports · 2017
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsNeonatal intensive care unitIntensive careProtocol (science)MedicineSingle-subject designIntensive care unitIntensive care medicinePediatricsPsychologyAlternative medicine

Abstract

fetched live from OpenAlex

REVIEW QUESTION/OBJECTIVE: The objective of this review is to identify the impact of single room neonatal intensive care unit (NICU) design on infant outcomes compared to alternative design.The specific question is: what is the impact of single room design on outcomes of infants cared for in intensive care units compared to those in alternative designs?

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)0.046
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.047
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.078
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0210.018
Bibliometrics0.0120.011
Science and technology studies0.0030.004
Scholarly communication0.0070.007
Open science0.0040.005
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0470.005

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 head0.407
GPT teacher head0.556
Teacher spread0.149 · 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 designSystematic review
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

Citations7
Published2017
Admission routes1
Has abstractyes

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