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Record W7126334687

Prevalencia de astenopia en niños escolares de 6 a 17 años, por el uso de dispositivos digitales durante la pandemia por COVID-19: revisión sistemática

2023· other· es· W7126334687 on OpenAlexaboutno aff
Jenny Paola Acosta Castellanos

Bibliographic record

VenueCiencia Unisalle (Universidad de La Salle) · 2023
Typeother
Languagees
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakMEDLINECoronavirus Infections
DOInot available

Abstract

fetched live from OpenAlex

El uso de dispositivos electrónicos es primordial en la vida cotidiana actual a nivel mundial y gracias a la emergencia sanitaria por COVID-19 se incrementó, pues fue necesario suspender actividades escolares presenciales obligando a los estudiantes a tomar clases virtuales, esto aumento la prevalencia de astenopia. Objetivo General: Determinar la prevalencia de astenopia en niños escolares de 6 a 17 años, por el uso de dispositivos digitales durante la pandemia por COVID-19. Método de investigación: Se realizó una revisión sistemática cualitativa mediante la pregunta PICOT; la búsqueda de literatura científica se realizó en Medline PubMed, Elsevier, Scielo, Scopus, Science direct, EBSCO, y JSTOR, con palabras clave en inglés y español, publicados entre 2020 y 2022. La calidad metodológica de los artículos se evaluó mediante herramientas como Newcastle-Ottawa para estudios trasversales y AMSTAR para revisiones sistemáticas, se incluyeron artículos de revisión, de investigaciones científicas, cualitativas, artículos de revistas y estudios de casos y controles, y/o estudios transversales, que abordaran el tema prevalencia de astenopia por uso de los dispositivos electrónicos en escolares, durante la pandemia del COVID-19. El reporte de la revisión se realizó con base en la declaración PRISMA.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.004
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0050.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.003

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 head0.011
GPT teacher head0.299
Teacher spread0.288 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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