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Travel Medicine Research Priorities: Establishing an Evidence Base

2010· article· en· W2091546598 on OpenAlexaff
Elizabeth A. Talbot, Lin H. Chen, Christopher Sanford, Anne McCarthy, Karin Leder

Bibliographic record

VenueJournal of Travel Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineTravel medicineBase (topology)MEDLINEFamily medicineIntensive care medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Travel medicine is the medical subspecialty which promotes healthy and safe travel. Numerous studies have been published that provide evidence for the practice of travel medicine, but gaps exist. METHODS: The Research Committee of the International Society of Travel Medicine (ISTM) established a Writing Group which reviewed the existing evidence base and identified an initial list of research priorities through an interactive process that included e-mails, phone calls, and smaller meetings. The list was presented to a broader group of travel medicine experts, then was presented and discussed at the Annual ISTM Meeting, and further revised by the Writing Group. Each research question was then subject to literature search to ensure that adequate research had not already been conducted. RESULTS: Twenty-five research priorities were identified and categorized as intended to inform pre-travel encounters, safety during travel, and post-travel management. CONCLUSION: We have described the research priorities that will help to expand the evidence base in travel medicine. This discussion of research priorities serves to highlight the commitment that the ISTM has in promoting quality travel-related research.

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)0.016
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.226
GPT teacher head0.479
Teacher spread0.253 · 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.

Study designBench or experimental
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

Citations30
Published2010
Admission routes1
Has abstractyes

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