Management of <i>C</i> <i>oxiella burnetii</i> infection in livestock populations and the associated zoonotic risk: A consensus statement
Bibliographic record
Abstract
Infections caused by Coxiella burnetii, commonly referred to as coxiellosis when occurring in animals and Query fever when occurring in humans, are an important cause of abortions, decreased reproductive efficiency, and subclinical infections in ruminants. The organism also represents an important zoonotic concern associated with its ability to aerosolize easily and its low infectious dose. Available diagnostic tests have limited sensitivity, which combined with the absence of treatment options in animals and limited approaches to prevention, result in difficulty managing this agent for optimal animal health and zoonotic disease outcomes. The purpose of this consensus statement is to provide veterinarians and public health officials with a summary of the available information regarding management of C. burnetii infection in livestock populations. A discussion of currently available testing options and their interpretation is provided, along with recommendations on management practices that can be implemented on-farm in the face of an outbreak to mitigate losses. Emphasis is placed on biosecurity measures that can be considered for minimizing the zoonotic transmission risk in both field and veterinary facilities.
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 | 0.026 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".