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Record W4402031392 · doi:10.58931/cect.2024.3348

Update on Giant Cell Arteritis: Essential Information for Ophthalmologists

2024· article· en· W4402031392 on OpenAlexaff
Laura Donaldson

Bibliographic record

VenueCanadian Eye Care Today · 2024
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGiant cell arteritisMedicineArteritisPathologyVasculitisDisease

Abstract

fetched live from OpenAlex

Giant cell arteritis (GCA) is an important cause of irreversible vision loss in the elderly population. For any physician, making this diagnosis can be difficult due to the highly variable clinical presentation of this large-vessel vasculitis. The 1990 American College of Rheumatology (ACR) classification criteria for GCA are frequently used, however, they were developed to classify GCA patients vs those with other forms of vasculitis and are not true diagnostic criteria. Despite the high predilection of GCA for ocular circulations, the original 1990 criteria did not include any signs or symptoms related to vision. The classification criteria were updated by the ACR and European Alliance of Associations for Rheumatology (EULAR) in 2022 with the significant inclusion of “Sudden vision loss” (Table 1).

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.734

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)0.0010.001

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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