Sarcoidosis: a prospective observational cohort from Northern Alberta.
Bibliographic record
Abstract
INTRODUCTION: Sarcoidosis is a multi-system disease reported to occur with a higher incidence in Alberta than many other health jurisdictions within and outside of Canada. The reasons for this higher incidence are currently not known. Exposure to beryllium can result in a clinically and radiologically identical disease to sarcoidosis. The purpose of our study was to identify patterns with potential occupational or environmental exposures to beryllium amongst individuals with sarcoidosis in Alberta through a tertiary referral center. METHODS: A prospective observational study was carried out at the University of Alberta Hospital. Patients with confirmed sarcoidosis (stages 0-4) were recruited from subspecialty clinics (Respirology, Cardiology, Neurology and Occupational Health). A predetermined list of industries thought to involve potentially relevant exposures for the development of sarcoidosis was used to capture current and previous exposure history. Results were entered into a database and where possible verified by comparing with existing electronic medical records (including histories, physical examination, diagnostic imaging and physiology). RESULTS: A total of 45 patients were recruited, 25 men and 20 women. Of these, 84% of participants reported working in or being exposed to an industry/environment suspected of contributing to development of sarcoidosis over their lifetime. The most frequently reported exposures were within farming and agriculture (27%), oil and gas (20%), metalworking and handling animals (18%). CONCLUSIONS: .
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".