Human and animal botulism surveillance in France from 2008 to 2019
Bibliographic record
Abstract
. This disease induces flaccid paralysis that can result in respiratory paralysis and heart failure. Due to its serious potential impact on public health, botulism is a closely monitored notifiable disease in France through a case-based passive surveillance system. In humans, this disease is rare, with an average of 10 outbreaks reported each year, mainly due to the consumption of contaminated foods. Type B and to a lesser extend type A are responsible for the majority of cases of foodborne botulism. Each year, an average of 30 outbreaks are recorded on poultry farms, about 20 cases in wild birds and about 10 outbreaks in cattle, involving a large number of animals. Mosaic forms C/D and D/C in birds and cattle, respectively, are the predominant types in animals in France. Types C and D have also been observed to a lesser extent in animals. With the exception of botulinum toxin E, which was exceptionally detected throughout the period in wild birds, the types of botulism found in animal outbreaks are different from those identified in human outbreaks over the last ten years in France and no human botulism outbreaks investigated have been linked to animal botulism. In line with the One Health concept, we present the first integrative approach to the routine surveillance of botulism in humans and animals in France.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".