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Record W6887670158 · doi:10.17605/osf.io/425vf

Care for Newborns and Infants in Mobile Emergency Care: SCOPING REVIEW

2024· other· en· W6887670158 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careContext (archaeology)MEDLINEPortugueseInclusion (mineral)Latin AmericansGrey literature

Abstract

fetched live from OpenAlex

objective Identify and synthesize scientific evidence on the care of newborns and infants in the Mobile Emergency Care Service. Question formulation P (Population) – newborns and infants; C (Concept) – care/assistance from the healthcare professional; C (Context) – Mobile Emergency Care Service. What healthcare professional care is relevant, in the context of the Mobile Emergency Care Service, to newborns and infants? What health professional behaviors are important in the Mobile Emergency Care Service for newborns and infants? Inclusion criteria Will be included: research published in full in English, Spanish and Portuguese; which deal with the care of healthcare professionals, in the context of the Mobile Emergency Care Service, for newborns and infants. Time limit, from Ordinance No. 1,600, of July 7, 2011; which reformulates the National Emergency Care Policy and establishes the Emergency Care Network in the Unified Health System (SUS), that is, from 2011. Exclusion criteria The following will be excluded: single case studies, editorials, experience reports, event annals, theoretical essays. Data collect Data base: - Cummulative Index to Nursing and Allied Health Literature (CINAHL); - Medline via National Library of Medicine and National Institutes of Health (PubMed); - Latin American and Caribbean Literature in Health Sciences (LILACS), - SCOPUS; - Web of Science; - Embase; - Cochrane Library. Search in gray literature: - CAPES Theses and Dissertations Catalog - DART-Europe E-Theses Portal - Electronic Theses Online Service (EThOS) - Portuguese Open Access Scientific Repository (RCAAP) - National ETD Portal - Theses Canada - Latin American Thesis Portal - World Cat Dissertations and Theses • Identification of descriptors and keywords Descriptors and keywords used in studies that address the topic of interest based on the combination of MeSH identified for the research mnemonic: (Infant, Newborn OR Infant, Premature OR Infant, Very Low Birth Weight OR Infant, Extremely Premature OR Infant, Large for Gestational Age OR Infant, Extremely Low Birth Weight OR Infant OR Infant Care OR Sudden Infant Death OR Infant, Postmature OR Brief, Resolved, Unexplained Event) AND (Care OR Patient Care Bundles OR Medical Care OR Critical Care Outcomes OR Critical Care OR Postnatal Care OR Intensive Care Units, Neonatal OR Subacute Care, OR Transitional Care, OR Secondary Care, OR Telemedicine Emergency Care OR Patient Care Management OR Therapeutic Approaches) AND (Ambulances OR Emergency Mobile Units OR Mobile Emergency Units OR Mobile Emergency Service OR Emergency medical assistance service OR Mobile Health Units OR Prehospital Care OR Emergency Medical Services OR Emergency Medicine OR SAMU).

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)0.011
metaresearch head score (Gemma)0.062
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 score0.018
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.062
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0180.017
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0030.003
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.032
GPT teacher head0.424
Teacher spread0.391 · 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
Published2024
Admission routes1
Has abstractyes

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