Managing ibd symptoms at work: a survey of workplace accommodations amongst individuals with IBD
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) has been found to adversely affect quality of life (QoL). The level of disability an IBD patient experiences can affect the overall QoL, although these are two distinct concepts. There is some overlap between disability scales and QoL indices, since both are reported subjectively by the patient, and certain domains (e.g. emotional) are measured similarly in both. In 1995-1996 we created the population based University of Manitoba IBD Research Registry. We continue to update this Registry and have done so most recently in the spring of 2014. There are 3800 persons with IBD in this Registry that we can contact for other research studies. We hypothesize that disability rates 10 years after diagnosis of IBD will be lower than what might be expected from a chronic immune mediated disease. We will mail out a survey and informed consent form to persons in the Research Registry. The survey will include psychological, employment and disability related tools. Participants will be asked to give consent to access their Manitoba Health administrative data. Using administrative health data we will be able to create a trajectory of the course of their disease and the type of prescription drugs (since 1995) that they have used. We will be able to determine if there are psychological variables, disease variables, and drug variables that are associated with reporting disability or unemployment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".