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Record W4229549877 · doi:10.15353/cjo.80.264

Canadian Association of Optometrists/Canadian Ophthalmological Society Joint Position Statement

2018· article· en· W4229549877 on OpenAlexvenueaboutno aff

Bibliographic record

VenueCanadian journal of optometry/CJO. Canadian journal of optometry · 2018
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPosition statementScope (computer science)Association (psychology)Statement (logic)Screen timeMedicineOptometryStatisticPediatricsPsychologyFamily medicineComputer sciencePolitical sciencePhysical activityPhysical therapy

Abstract

fetched live from OpenAlex

The prevalence of electronic screen-related ocular symptoms in adult users is estimated to be as high as 50–90%. While the corresponding statistic in children is not known, the use of electronic screens by children has become more commonplace (at both home and school), begins earlier in childhood than in the past, and can last for long periods of time. The prevalence of electronic-screen symptoms in adults and the resultant guidelines for safe use should not be automatically applied to children. The visual and physical systems of children are different than those of adults, and still developing. In addition, children use screens differently and for different tasks. This policy reviews the current literature on ocular and visual symptoms related to electronic-screen use in children and provides evidence-based guidelines for safe use. The effect of screen-time on other cognitive and developmental milestones is beyond the scope of this statement.

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)0.006
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.505

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0650.018

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 head0.018
GPT teacher head0.333
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations10
Published2018
Admission routes2
Has abstractyes

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Same venueCanadian journal of optometry/CJO. Canadian journal of optometrySame topicErgonomics and Musculoskeletal DisordersFrench-language works237,207