MétaCan
Menu
Back to cohort
Record W2039641355 · doi:10.1016/j.aogh.2014.08.038

Undergraduate and graduate student training in global health research: Preparing the next generation

2014· article· en· W2039641355 on OpenAlexaboutno aff
Katherine McDaniel, Katherine Standish, Kaveh Khoshnood, Meredith Mira

Bibliographic record

VenueAnnals of Global Health · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Medical educationGraduate studentsPsychologyMedicineGeographyMeteorology

Abstract

fetched live from OpenAlex

Structure/Method/Design: For the period from January 2012 to December 2013, multidisciplinary teams that included medical students and residents from hospitals in Canada and the United States, mobilized bimonthly, and conducted outreach clinics in five rotating communities seeing 80 to 160 children daily for 1 week.All participants were required to have predeparture training and protocols were developed to ensure consistent diagnosis and treatment of common conditions in children.Statistics were collected for each day and location.Results (Scientific Abstract)/Collaborative Partners (Programmatic Abstract): Haiti Village Health Haitian Ministry of Health Summary/Conclusion: The data obtained for the years 2012 and 2013 were compared for all children seen from newborn to age 15 years.There were five outreach programs from four different hospital and residency programs in each year conducted in the same months each year.There was an equal amount of patients served in both years with a similar sex and age distribution.The data for the top 12 most common diagnoses were reviewed and compared over this 2-year period.A total 4825 distinct diagnosis in 4133 patients were reviewed and compared.There was no significant difference found between the rate of recorded diagnoses in the years 2012 and 2013.Results were consistent across all diagnostic categories and independent of team composition.A protocol-based global child health approach is effective at improving the accuracy of diagnosis and treatment among medical trainees of varying experience and from multiple training programs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.855
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.433
GPT teacher head0.523
Teacher spread0.090 · 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 teacher head, 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of Global HealthSame topicGlobal Health and SurgeryFrench-language works237,207