Virus de la Enfermedad de Marek: aproximación molecular al virus y respuesta inmune del hospedero
Bibliographic record
Abstract
Marek’s disease virus affects dramatically the production of broiler chicken,hens breeding and commercial due to lost causes for carcass condemnation,presence of tumors and high mortality. Give them us derivativesby the VEM they affect significant economic losses in the poultry industryworldwide and impact the comprehensive management of poultry healthand health in general. The genetic and molecular characteristics of theVEM highlight the diversity of the genome in each of the 3 serotypes of thevirus; genes involved in pathogenicity, evasion of the immune responseand replication strategies are consistent with the difficulty of their infectioncontrol. Viral latency and the pump of the immune response of thehost, particularly the control of type I interferons, are the mechanism tohelp the perpetuation in the poultry and thus hamper their effective environmentalcontrol. All those conditions have allowed that the virus evolvesto forms more virulent that with the use of the vaccines current does notprovide a protection adequate against these; for this reason, it is necessaryto reconsider current vaccination plans to improve the immune responseof active type, particularly involving cell type, to control his evasion andcontrol on the immune system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".