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Record W4386376955 · doi:10.1016/j.jtos.2023.08.009

TFOS Lifestyle Report Executive Summary: A Lifestyle Epidemic - Ocular Surface Disease

2023· review· en· W4386376955 on OpenAlexaff
Jennifer P. Craig, Mônica Alves, James S. Wolffsohn, Laura E. Downie, Nathan Efron, Anat Galor, José Álvaro Pereira Gomes, Lyndon Jones, Maria Markoulli, Fiona Stapleton, Christopher E. Starr, Amy Gallant Sullivan, David A. Sullivan

Bibliographic record

VenueThe Ocular Surface · 2023
Typereview
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
FundersAllerganSeqirusSantenCooperVision
KeywordsMedicineNarrative reviewDiseasePathologyIntensive care medicine

Abstract

fetched live from OpenAlex

The Tear Film & Ocular Surface Society (TFOS) Workshop entitled 'A Lifestyle Epidemic: Ocular Surface Disease' was a global initiative undertaken to establish the direct and indirect impacts of everyday lifestyle choices and challenges on ocular surface health. This article presents an executive summary of the evidence-based conclusions and recommendations of the 10-part TFOS Lifestyle Workshop report. Lifestyle factors described within the report include contact lenses, cosmetics, digital environment, elective medications and procedures, environmental conditions, lifestyle challenges, nutrition, and societal challenges. For each topic area, the current literature was summarized and appraised in a narrative-style review and the answer to a key topic-specific question was sought using systematic review methodology. The TFOS Lifestyle Workshop report was published in its entirety in the April 2023 and July 2023 issues of The Ocular Surface journal. Links to downloadable versions of the document and supplementary material, including report translations, are available on the TFOS website: http://www.TearFilm.org.

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)0.012
metaresearch head score (Gemma)0.020
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: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0070.010
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0300.006

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 head0.049
GPT teacher head0.341
Teacher spread0.292 · 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

Citations50
Published2023
Admission routes1
Has abstractyes

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