Bibliographic record
Abstract
Infection in animals and humans from the bacterium Coxiella burnetii is responsible for significant disease risk. In sheep and goats it is an important cause of abortion, stillbirth, and neonatal weakness and mortality, although the organism may be present and shed in birth fluids, milk and feces without signs of disease. Infection in these species, as well as cattle, is widespread. Humans who work with infected ruminants are at risk of developing mild to severe disease, called Q fever. Chronic Q fever is particularly dangerous, with a high case fatality rate. Treatment with antimicrobials to control abortion or reduce bacterial shedding is unrewarding in sheep and goats. Vaccination has been shown to reduce abortions and degree of shedding, but currently no vaccine is licensed in the US or Canada. Measures to lower risk of infection in humans include lowering the level of contamination of the environment with the bacteria, understanding the signs in people so that treatment can be given promptly, and using protective wear to reduce exposure. This is an important zoonosis, and education of clients and service providers is a critical component of reducing the risk of Q 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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.070 | 0.025 |
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".