Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RATIONALE FOR REVIEW: In response to increased concerns about emerging infectious diseases, GeoSentinel, the Global Surveillance Network of the International Society of Travel Medicine in partnership with the US Centers for Disease Control and Prevention (CDC), was established in 1995 in order to serve as a global provider-based emerging infections sentinel network, conduct surveillance for travel-related infections and communicate and assist global public health responses. This review summarizes the history, past achievements and future directions of the GeoSentinel Network. KEY FINDINGS: Funded by the US CDC in 1996, GeoSentinel has grown from a group of eight US-based travel and tropical medicine centers to a global network, which currently consists of 68 sites in 28 countries. GeoSentinel has provided important contributions that have enhanced the ability to use destination-specific differences to guide diagnosis and treatment of returning travelers, migrants and refugees. During the last two decades, GeoSentinel has identified a number of sentinel infectious disease events including previously unrecognized outbreaks and occurrence of diseases in locations thought not to harbor certain infectious agents. GeoSentinel has also provided useful insight into illnesses affecting different traveling populations such as migrants, business travelers and students, while characterizing in greater detail the epidemiology of infectious diseases such as typhoid fever, leishmaniasis and Zika virus disease. CONCLUSIONS: Surveillance of travel- and migration-related infectious diseases has been the main focus of GeoSentinel for the last 25 years. However, GeoSentinel is now evolving into a network that will conduct both research and surveillance. The large number of participating sites and excellent geographic coverage for identification of both common and illnesses in individuals who have traversed international borders uniquely position GeoSentinel to make important contributions of travel-related infectious diseases in the years to come.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it