© 2003 Canadian Medical Association or its licensors
Bibliographic record
Abstract
In 1998, I signed up for a 2-year commitment with theUnited Nations Volunteers, a division of the UnitedNations Development Program, seeking excitementand a different perspective on pathology practice. Fresh out of fellowship, I looked forward to the challenges of working in a region short on pathologists, far from the comforting embrace of a First World teaching hospital. I travelled to western Jamaica to become the only pathologist in Montego Bay, at a 500-bed regional hospital with a catchment population of almost half a million. I worked 12-hour days, 7 days a week. My time was fully occupied with examining surgical pathology specimens, set-ting up a fine-needle aspiration practice, looking after labo-ratory administration and conducting autopsies. It was while I was preparing for an autopsy shortly af-ter my arrival that my First World notions of the nature of the pathologist–patient relationship were challenged. Assuming that all I had to do was to issue a preliminary report after the autopsy with a carefully worded statement about the potential cause of death, I was astonished when the deceased’s relatives demanded to be present during the procedure. The patient, an elderly man with a long history of heart disease, had died a day earlier. His rela-tives were concerned that he had not received proper medical care and did not believe that he had had cardiac problems. The hospital’s administrators assured me that this was an acceptable practice. I explained the conduct that was ex-pected during an autopsy to the family. My team and I passed out masks to the 4 relatives who would observe the autopsy and then proceeded with the dissection. Not one of them flinched during the procedure. I showed them the en-larged heart with a thickened left ventricle, the severely oc-cluded, calcified coronary vessels and heavy lungs and ex-Pathologists going “live”: lessons from a developing country on giving a human face to pathology
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.771 | 0.701 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".