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Record W2066553824 · doi:10.1097/wno.0b013e3181dfa982

Vision and Driving: Canada

2010· review· en· W2066553824 on OpenAlexaffabout
Payam Yazdan-Ashoori, Martin ten Hove

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2010
Typereview
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsLicensureLicenseNova scotiaOptometryGeographyMedicinePolitical scienceMedical educationLaw

Abstract

fetched live from OpenAlex

Supported by the findings of a major review of vision standards for driving in Canada, the Canadian Ophthalmological Society's Committee on Vision Standards for Driving issued a series of recommendations in 2000 to the Canadian Medical Association. Many of these recommendations, including changes in visual acuity and visual field standards and consideration for exceptional cases, have been implemented across Canada. Canadian courts have stated that it is important to provide on-road assessments for visually impaired individuals who wish to continue driving. Most Canadian provinces and territories will allow visually impaired drivers a license if they pass the test. However, these on-road assessments use scarce resources and may be expensive for the driver. Limited licensure is a widespread practice, but whether it effectively protects drivers is not established. Except for Alberta, Quebec, and Nova Scotia, all Canadian provinces and territories have legislated mandatory reporting of visually impaired drivers by vision care providers.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.112
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.013
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.084
GPT teacher head0.461
Teacher spread0.377 · 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
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

Citations32
Published2010
Admission routes2
Has abstractyes

Explore more

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