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Record W2617246444 · doi:10.3389/fpubh.2017.00112

Internal Medicine Residency Program in Guyana: A Collaborative Model for Sustainable Graduate Medical Education in Resource-Limited Settings

2017· article· en· W2617246444 on OpenAlexaff
Dev Persaud, Joanna Cole, Ramdeo Jainarine, Zahira Khalid

Bibliographic record

VenueFrontiers in Public Health · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCurriculumMedical educationCorporationResource (disambiguation)MedicineProgram evaluationPolitical scienceComputer sciencePublic administration

Abstract

fetched live from OpenAlex

The Georgetown Public Hospital Corporation (GPHC) started the Internal Medicine/Infectious Diseases residency program in 2013. It was a collaborative initiative between GPHC and University of Maryland. Since that time the program has gone through many trials and developed new partnerships and collaboration and emerged as a young successful program with close international links that have worked and persevered in developing the successful academic and professional careers of its residents. International collaborations have resulted in applying innovative methods of teaching to deliver the curriculum in a sustainable manner in a resource-limited setting. The article discusses in detail the history of the program and the roles that the collaborative partners have played in the evolution of the program.

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)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0050.002
Open science0.0020.016
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.084
GPT teacher head0.359
Teacher spread0.275 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2017
Admission routes1
Has abstractyes

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