An example of one health approach: a timeline of the history of trichinellosis control
Bibliographic record
Abstract
Trichinellosis is the first zoonosis for which a detection at the slaughterhouse is mandatory. The delay between the description of the parasite in 1835 (Owen and Paget), first finding in pork in 1846 (Leidy), deciphering of the cycle in 1858 (Virchow), its demonstration as a pathogenic agent in 1860 (Zenker), and the implementation of a control in pork in the duchy of Brunswick (Germany) in 1863 was rather short. This control led to a dramatic decrease in lethal cases in Germany. Around 1880, most European countries claimed that massive importations of pork from the USA could be sources of trichinellosis. Therefore, the USA was obliged to check on an industrial scale that all exported pork was Trichinella free. In the 20th century, several institutions played a crucial role in the control of trichinellosis: the USDA in Beltsville (deep-freezing killing of larvae, controls in farms, digestion techniques and antigenic preparations), the RIVM in Bilthoven (ELISA), the ISS in Rome (clarification of the different species of Trichinella. The ANSES (Maisons-Alfort, France) performed horse experimental infections and, with the CFIA (Saskatoon, Canada) developed quality control assurance, proficiency samples, and technician training". The International Commission on Trichinellosis (ITC) (created in 1960) was a key tool to develop collaborations and issue recommendations on control and Trichinella-free farming.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".