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Record W7028518705

Fellows serving in Afghanistan thank Royal College with special gift

2013· article· en· W7028518705 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsSpecialtyCurriculumExecutive directorFlag (linear algebra)Vice presidentBlueprint
DOInot available

Abstract

fetched live from OpenAlex

In recognition of support given to Fellows serving in Afghanistan, a flag box was commissioned by officers and recently presented to the Royal College. Past-President Louis Francescutti, 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, the flag box is engraved with the Royal College crest, as well as with the Canadian and Afghani national flags. It will be displayed in the Roddick Room — the Royal College’s library. For over a decade, many Fellows of the Royal College, both civilians and Canadian Armed Forces specialist medical officers, have worked at the hospital on Kandahar airfield, tending to 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 addition to NATO soldiers. In 2012, the mission moved to Kabul with a new focus on the reconstruction of Afghanistan’s postgraduate medical education system. The medical officers recently helped develop training materials and curriculum for residency programs in eight specialty disciplines. Ken Harris, MD, FRCSC, executive director, Office of Education at the Royal College, was a valuable resource, extending his expertise, guidance and feedback to the group. (Dialogue 2013; 13 (6): 18-19)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.183
Threshold uncertainty score0.611

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.002
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.1830.089

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.

Opus teacher head0.064
GPT teacher head0.305
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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