The Collaborative Ocular Tuberculosis Study (COTS) Consensus (CON) Group Meeting Proceedings
Bibliographic record
Abstract
An international, expert led consensus initiative was set up by the Collaborative Ocular Tuberculosis Study (COTS) group to develop systematic, evidence, and experience-based recommendations for the treatment of ocular TB using a modified Delphi technique process. In the first round of Delphi, the group identified clinical scenarios pertinent to ocular TB based on five clinical phenotypes (anterior uveitis, intermediate uveitis, choroiditis, retinal vasculitis, and panuveitis). Using an interactive online questionnaires, guided by background knowledge from published literature, 486 consensus statements for initiating ATT were generated and deliberated amongst 81 global uveitis experts. The median score of five was considered reaching consensus for initiating ATT. The median score of four was tabled for deliberation through Delphi round 2 in a face-to-face meeting. This report describes the methodology adopted and followed through the consensus process, which help elucidate the guidelines for initiating ATT in patients with choroidal TB.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.179 | 0.120 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".