Canadian Pain Society Conference
Bibliographic record
Abstract
BRIEF DESCRIPTION: Voices of People with Pain is a public event open to pain sufferers, their families, their caregivers and the general public.This event features the stories of people living with pain as told in their own words and will put a face to the serious nature of pain.Untreated or undertreated pain is our nation's leading public health problem and the only way to move forward is to heighten the public's awareness about the impact pain has on those who suffer, their families and our health care leaders.The presentation covers three basic areas that pain sufferers experience on their journey through pain.As Thomas Jefferson said, "The art of life is the art of avoiding pain; and he is the best pilot, who steers clearest of the rocks and shoals with which it is beset."This leads to the premise of the presentation as follows:• Chronic pain can happen to anyone.It does not discriminate.It affects people of all stages of life -the young, the middle-aged and the elderly.• Not treating pain or believing it does not exist causes serious problems.Pain weakens the immune system and slows recovery from disease or injury.It diminishes quality of life and impacts almost every aspect of a person's life.• People in pain can lead a productive life and contribute to society.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.214 | 0.030 |
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".