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Record W2164471750 · doi:10.1086/421268

Globalization of Infectious Diseases: The Impact of Migration

2004· article· en· W2164471750 on OpenAlexaff
B. D. Gushulak, Douglas W. MacPherson

Bibliographic record

VenueClinical Infectious Diseases · 2004
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePopulationPublic healthHealth carePsychological interventionEnvironmental healthCompetence (human resources)GlobalizationGeographic mobilityEconomic growthNursingPolitical science

Abstract

fetched live from OpenAlex

With up to 2% of the world's population living outside of their country of birth, the potential impact of population mobility on health and on use of health services of migrant host nations is increasing in its importance. The drivers of mobility, the process of the international movement, and the back-and-forth transitioning between differential risk environments has significance for the management of infectious diseases in migrant receiving areas. The management issues are broad, high-level, and cross-cutting, including policy decisions on managing the migration process for skilled-labor requirements, population demographic and biometric characteristics, and family reunification; to program issues encompassing health care professional education, training, and maintenance of competence; communication of global events of public health significance; development of management guidelines, particularly for nonendemic diseases; access to diagnostic and therapeutic interventions for exotic or rare clinical presentations; and monitoring of health service use and health outcomes in both the migrant and local populations.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0000.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.032
GPT teacher head0.419
Teacher spread0.387 · 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
GenreReview

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

Citations208
Published2004
Admission routes1
Has abstractyes

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