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Record W4299140526 · doi:10.4103/sjopt.sjopt_203_21

Biochemical and molecular alterations and potential clinical applications of biomarkers in keratoconus

2022· article· en· W4299140526 on OpenAlexaff
Vaitheeswaran G. Lalgudi, Rohit Shetty, Kanwal Nischal, Setareh Ziai, Mona Koaik, Swaminathan Sethu

Bibliographic record

VenueSaudi Journal of Ophthalmology · 2022
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsChildren's Hospital of Eastern OntarioOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsKeratoconusMedicineDiseaseCorneal diseaseBioinformaticsQuality of life (healthcare)Intensive care medicineCorneaOphthalmologyPathologyBiology

Abstract

fetched live from OpenAlex

Keratoconus (KC) is a complex multifactorial corneal ectatic disorder, with disease onset commonly in the second-third decades significantly affecting quantity, quality of vision, and quality of life. Several pathways and factors such as eye rubbing, inflammatory, oxidative, metabolic, genetic, and hormonal among others have been studied in the last two decades. However, the management of KC is still based on a few "one-size fits all" approaches and is predominantly guided by topo/tomographic parameters. Consideration of the several novel factors which have the potential to be biomarkers in addressing several unanswered questions in the disease process could help in the better predictive ability of progression or vision loss and customization of treatment options. This article delves into the understanding of these novel factors or biomarkers based on the pathogenesis of KC and features a special focus on their potential clinical applications and their future role in personalized medicine.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.331
Teacher spread0.312 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations12
Published2022
Admission routes1
Has abstractyes

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