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The History of Optometry Journals from a Bibliometric Perspective

2024· article· en· W4395688247 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHindsight · 2024
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Health Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIndex (typography)PublishingLibrary sciencePerspective (graphical)OptometryMedicinePolitical scienceLawArtComputer scienceVisual arts

Abstract

fetched live from OpenAlex

The rich history of optometric journal publications has been well documented, but the scientific impact of all optometry journals over all time has not been published. This work aims to determine the most impactful papers, authors, institutions and countries publishing in optometry journals. A h-index for “optometry journal publications” (the “hOJP-index”) was derived for each constituent of each category to serve as a measure of impact. The hOJP-index for the 34,565 papers published in all optometry journals is 136; these papers have been cited 294,239 times. Optometry and Vision Science is the most impactful and prolific journal (hOJP=118; n=13,095 papers). The most highly cited paper, by Richard Armstrong, is entitled “When to use the Bonferroni correction” (1,172 citations). Australian optometrist Nathan Efron is the most impactful and prolific author (hOJP=41; n=273). UNSW Sydney and the University of California, Berkeley are the most impactful institutions (both hOJP=58), and UNSW Sydney is the most prolific (n=963). The most impactful and prolific nation is the United States (hOJP=109; n=12,050). This quantitative bibliometric analysis demonstrates an impactful optometric research base enshrined in optometry journals.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.014
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.186
GPT teacher head0.558
Teacher spread0.371 · 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