Fellows serving in Afghanistan thank Royal College with special gift
Bibliographic record
Abstract
In recognition of support given to Fellows serving in Afghanistan, a flag box wascommissioned by officers and recently presented to the Royal College. Past-President LouisFrancescutti, MD, FRCPC, himself an Honorary Colonel of 1 Field Ambulance Edmonton,accepted the gift on behalf of the organization. Crafted by the Udin brothers of Kabul, theflag box is engraved with the Royal College crest, as well as with the Canadian and Afghaninational flags. It will be displayed in the Roddick Room — the Royal College’s library.Helping locals regain health, rebuild health careFor over a decade, many Fellows of the Royal College, both civilians and Canadian ArmedForces specialist medical officers, have worked at the hospital on Kandahar airfield, tendingto victims of the conflict. The hospital, commanded by Canadian Forces Health Services,provided care for civilian Afghans and injured members of their security forces, in additionto NATO soldiers. In 2012, the mission moved to Kabul with a new focus on thereconstruction of Afghanistan’s postgraduate medical education system. The medical officersrecently helped develop training materials and curriculum for residency programs in eightspecialty disciplines. Ken Harris, MD, FRCSC, executive director, Office of Education at theRoyal College, was a valuable resource, extending his expertise, guidance and feedback tothe group
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.345 | 0.186 |
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".