Pathologists as Leaders, Innovators, and Devoted Physicians: Special Section on Pathology in Resource-Poor Nations
Bibliographic record
Abstract
Many of our colleagues in pathology, including many members of the College of American Pathologists (CAP), volunteer their time and talent to patients in resource-poor nations, which may involve single tours or longstanding commitments in these countries. Not only can physical deprivations exist in these localities, but political or criminal violence also are risks in some areas. Far from being timid recluses who anonymously issue reports from basement laboratories, many of our pathology colleagues are warriors on the front lines of medical care in the world's most destitute and dangerous places. Too often, we fail to recognize the pathologists who engage in these humanitarian efforts and the organizations that support these efforts, of which the CAP Foundation (www.foundation.cap.org, accessed October 20, 2010) is a major contributor.1In this issue of the Archives of Pathology & Laboratory Medicine, Hallgrimur Benediktsson, MD, FRCPC, section editor for “Global Health,” has organized a special section that had its origins in the Archives' participation with more than 215 other biomedical journals in the 2007 global theme issue on Poverty and Human Development 2,3 and in a symposium at the Canadian Association of Pathologists annual meeting in Ottawa in July 2008. The articles in this special section differ from our usual articles in that they focus on potential solutions to daunting challenges to the practice of pathology in resource-poor nations, on investigations of diseases unique to their populations, and on inspirational personal experiences of pathologists in these settings. This series of articles is instructive in several ways, particularly because it highlights pathologists as innovators, problem-solvers, and dedicated clinicians. There are lessons for all of us to learn for our practices and for our personal and professional lives. We hope that this special section will bring attention to the energetic leadership role that pathologists can take as devoted physicians in an uncertain, hazardous world.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.016 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".