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Record W4410796240 · doi:10.1016/j.ajo.2025.05.038

TFOS DEWS III Editorial

2025· review· es· W4410796240 on OpenAlexaff
Victor L. Perez, Wei Chen, Jennifer P. Craig, Murat Doğru, Lyndon Jones, Fiona Stapleton, James S. Wolffsohn, David A. Sullivan

Bibliographic record

VenueAmerican Journal of Ophthalmology · 2025
Typereview
Languagees
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
FundersAbbVieTear Film and Ocular Surface Society
KeywordsOptometryMedicineOphthalmology

Abstract

fetched live from OpenAlex

The Tear Film & Ocular Surface Society (TFOS), a non-profit organization, was created to advance the research, literacy, and educational aspects of the scientific field of the tear film and ocular surface. Since its incorporation in 2000, TFOS has launched numerous global initiatives. Perhaps the best-known are the TFOS Workshops, especially those related to dry eye disease (DED). DED afflicts hundreds of millions of people worldwide, is a leading cause of patient visits to eye care practitioners, and, if moderate or severe, is associated with significant pain, role limitations, low vitality and poor general health.

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)0.003
metaresearch head score (Gemma)0.012
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.058
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0580.025

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 head0.020
GPT teacher head0.344
Teacher spread0.325 · 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
GenreEditorial

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

Citations5
Published2025
Admission routes1
Has abstractyes

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