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Record W2102912586 · doi:10.3201/eid1908.121739

Travel-associated Diseases, Indian Ocean Islands, 1997–2010

2013· article· en· W2102912586 on OpenAlexfundno aff
Hélène Savini, Philippe Gautret, Jean Gaudart, Vanessa Field, Francesco Castelli, Rogelio López‐Vélez, Poh Lian Lim, Marc Shaw, Frank von Sonnenburg, Louis Loutan, Fabrice Simon

Bibliographic record

VenueEmerging infectious diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsnot available
FundersCenters for Disease Control and PreventionNational Institutes of HealthUniversità degli Studi di BresciaUniversity of Cape TownUniversité de GenèveJohns Hopkins UniversityMahidol UniversityEmory UniversityUniversity of TorontoUniversiteit van AmsterdamUniversity of OttawaMcGill UniversityUniversity of MinnesotaHarvard UniversityUniversity of Washington
KeywordsChikungunyaMalariaOutbreakIndian oceanDiarrheaGeographyVirologyDengue feverChikungunya feverMedicineEnvironmental healthImmunologyInternal medicineOceanography

Abstract

fetched live from OpenAlex

Data collected by the GeoSentinel Surveillance Network for 1,415 ill travelers returning from Indian Ocean islands during 1997-2010 were analyzed. Malaria (from Comoros and Madagascar), acute nonparasitic diarrhea, and parasitoses were the most frequently diagnosed infectious diseases. An increase in arboviral diseases reflected the 2005 outbreak of chikungunya fever.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.008
GPT teacher head0.260
Teacher spread0.252 · 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; both teacher heads agree on what is shown here.

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

Citations21
Published2013
Admission routes1
Has abstractyes

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