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Record W4409147932 · doi:10.1002/14651858.cd016181

In-hospital motor interventions to reduce neurodevelopmental impairment in preterm infants: a scoping review

2025· review· en· W4409147932 on OpenAlexaff
Anna Badura, Michelle Fiander, Anna Gabriel, Matteo Pirinu, Laura Beccani, Roger F. Soll, Jane Cracknell, Dirk Faas, Sven Wellmann, Matteo Bruschettini

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsCochrane
Fundersnot available
KeywordsPsychological interventionMedicineModalitiesIntervention (counseling)PopulationMEDLINEIntensive care medicinePediatricsPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: This is a protocol for a Cochrane Review (prototype). The objectives are as follows: The aim of this scoping review is to map the quantitative literature about in-hospital motor interventions used to reduce neurodevelopmental impairment in preterm infants. We will collate information about the features, delivery mechanisms, objectives, providers, underlying theoretical frameworks, hypothesized or reported outcomes of these interventions, and equity characteristics of the population. The goal will be to document the breadth and characteristics of available evidence and to identify gaps or areas of knowledge in the field of motor interventions. Subcategories: Identify motor interventions initiated during neonatal intensive care unit stays for preterm infants Identify techniques, elements, and modalities in each intervention Determine the theories underlying these interventions Describe the extent to which the interventions are parent-centered Synthesize and categorize the different motor interventions.

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)0.023
metaresearch head score (Gemma)0.063
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: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.063
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0090.009
Bibliometrics0.0170.016
Science and technology studies0.0020.001
Scholarly communication0.0060.004
Open science0.0030.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.069
GPT teacher head0.412
Teacher spread0.343 · 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
GenreReview

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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