MétaCan
Menu
Back to cohort

Epidemiology of Transmissible Diseases after Elimination

2000· review· en· W1987172805 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Journal of Epidemiology · 2000
Typereview
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsUniversité LavalInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsOutbreakEpidemiologyMeaslesPopulationEnvironmental healthMedicineTransmission (telecommunications)VaccinationDiseaseDemographyVirology

Abstract

fetched live from OpenAlex

Elimination of an infectious disease is often understood to mean the total absence of cases in a population. This situation can occur only if the entire population is immune as a result of either natural disease or vaccination. However, this costly and unrealistic scenario is not necessary to ensure elimination, more appropriately defined as a situation in which sustained transmission cannot occur and secondary spread from importations of disease will end naturally, without intervention. The authors describe the size and duration of outbreaks caused by imported infections after indigenous transmission has been eliminated. They show that the status of the elimination process can be monitored by assessing the proportion of cases imported and the distribution of outbreak sizes. Measles in Canada, the United States, and the United Kingdom provides a good example of the relevance of these criteria. Surveillance of the size and duration of these outbreaks enables maintenance of elimination to be monitored.

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 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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.002
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.424
Teacher spread0.348 · 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