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Record W2077816287 · doi:10.4269/ajtmh.2011.11-0323

Review and Assessment of the American Society of Tropical Medicine and Hygiene Travel Awards Program, 1991–2010

2011· article· en· W2077816287 on OpenAlexaboutno aff
James W. Le Duc, Judy DeAcetis

Bibliographic record

VenueAmerican Journal of Tropical Medicine and Hygiene · 2011
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious Diseases
KeywordsGovernment (linguistics)Latin AmericansTropical medicineHygienePolitical scienceEconomic growthSocioeconomicsMedicineSociologyLawEconomics

Abstract

fetched live from OpenAlex

During 1991-2010, 456 persons from 62 countries were provided financial support to attend the annual meeting of the American Society of Tropical Medicine and Hygiene. Winners came from 17 African, 16 Asia-Pacific, 14 Latin American and Caribbean, and 13 European and Middle Eastern countries, and from Canada and the United States. Virtually equal numbers of awards were offered to women and men. Winners were selected from U.S. academic centers (30%), foreign universities (26%), international centers, institutes or research units (30%), and approximately 5% from U.S. government agencies. Almost all winners (73 of 76, 96%) had scientific publications subsequent to receiving the travel award. Less than 10% of award winners continued their membership in the Society after their one-year complementary membership. Winners indicated that the travel awards program facilitated international exchange and fostered collaborations between Society members and international scientists.

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)0.013
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.020
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.063
GPT teacher head0.379
Teacher spread0.317 · 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.

Study designObservational
DomainIncentives
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

Citations4
Published2011
Admission routes1
Has abstractyes

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