Use of organic acids blends on the control of Salmonella Heidelberg in Broilers
Bibliographic record
Abstract
With the increased population density, as well as human demographic changes, reporting has been increasingly, the incidence of food-borne illnesses being Salmonella, the main cause of the schedule of food poisoning outbreaks. Several countries as United States of America, Canada and European Union have as the main causative agent of food poisoning the. In Brazil, in the last decade Salmonella bacteria was the main cause of foodborne illness. The Salmonella bacteria is a Gram-negative bacillus, non-spore-forming and due to biochemical differences subdivided into two species: Salmonella bongori and Salmonella enterica and the last subdivided into six subspecies: enterica, salamae, arizonae, diarizonae, houtenae and indica. The Salmonella enterica entérica serovar Heidelberg is a major serovars found in birds that is related to salmonellosis in humans. In recent years the main way to control diseases bacterians was the use of antibiotics. The widespread use of these drugs as a preventive tool has been widely questioned, as are appearing pathogenic bacteria sensitive to antibiotics in several parts of the world. The prohibition of various antibiotics in modern poultry industry has generated the need to develop new ways of controlling bacterial infections and also the improvement in the performance of birds. The organics acids has been widely used in modern poultry industry for this purpose and have the main mechanism of action, antimicrobial activity, due to reduction of the pH within the microbial cell acting as bacterial growth inhibitors. But there are no studies to prove that organic acids, or which mixture of organic acids that are most effective for each type of Salmonella. In this context, the objective of this study is to address through a literature review the importance of Salmonella in public health and organic acids as relevant Salmonellosis control tool, especially in Salmonella control Heidelberg. A second objective is to create a chapter with an article entitled: "Use of organic acids blend in the control of Salmonella Heidelberg in Broiler Chickens ".
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".