Linfadenite caseosa em ovinos abatidos sob inspeção federal no estado do Rio Grande do Sul - estimativas de perdas/ Caseous Lymphadenitis in Sheep Slaughtered under Federal Inspection in the State of Rio Grande do Sul - Estimation of Losses
Bibliographic record
Abstract
Background: Caseous lymphadenitis (CL) is considered one of the most important diseases, economically, in sheep and goats in the United States, Canada and Australia. Annual losses in wool production reaches 17 million dollars in Australia, the disease cause important impact in Europe, Africa, Middle East, Australia, and in the Americas. The CL is a chronic disease, which affects mainly sheep and goats. The etiologic agent is the Corynebacterium pseudotuberculosis. The presence of the agent in feces contributes to environmental contamination and increases the risk of infections in herds. For countries with international marketing of live animals, the CL is a serious health problem to livestock disease-free. The objective of this study was to report the occurrence of lesions caused by CL in sheep slaughtered under the official service of inspection of the state of Rio Grande do Sul and correlate it to the economic losses due to the lesions found. Materials, Methods & Results: Data concerning the fate of raw materials, the total number of animals slaughtered and injuries from the ante and post-mortem were provided by the Federal Inspection Service (SIFs do Ministerio da Agricultura, Pecuaria e Abastecimento no Rio Grande do Sul (SFA/MAPA-RS). Data from the slaughtered animals were generated by the information system management service inspection (SIGSIF), requested in official character, which included the daily slaughter maps, as well as monthly and annual reports. Were collected data from 932,547 sheep slaughtered under federal inspection, from January 2004 to August 2009. The number of cases recorded only in Federal Inspection Service was 348 and the number of animals condemned at slaughter was 86.[...](AU)
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".