The Present of Scrapie and the Result of Breeding Program in Europe and Cyprus
Bibliographic record
Abstract
Scrapieis a fatal neuro-degenerative disease of sheep and goats belongs to the groupof transmissible spongiform encephalopathy (TSEs). Classical scrapie resistanceand susceptibility are closely related to PrP Gene polymorphism (ARR, ARQ, VRQ,and AHQ ARH) in sheep. The ARR / ARR genotype is the most resistant. Subsequentannual testing campaigns among the animals at risk were done in Europe from2001 to 2015 showed that the goat had at least 16 silent mutation of a specificstudy of PrP distribution. In 2014, the test in sheep and goats carried outunder the frame work of the TSE monitoring programs in E.U showed that 1.015out 325.530 sheep and 1.437 out of 127.016 goats turned out positive to classicalScrapie. There are Scrapie cases reported in both south and north Cyprus.Infected herds in Southern Cyprus represent 22.6% (2014) of total active sheepand goat herds. It has been also known that there are Scrapie cases in NorthernCyprus although there is no official data recorded. Some sheep breeds have thehighest ARR / ARR allele like Canadian Arcott with 39.3%, Dorset Down with28.9%, and Polypay with 26.8%. Among the sheep breeds, the Chios has thehighest level of ARR allele with 38% in Turkey and 32.5% in North Cyprus whilethe lowest level (5.9%) was seen in Awassi in Turkey. In the TSE eradicationprogram applied in Europe (2015): 1.When BSE cannot be excluded, all animals> 18 months killed for destruction shall be tested for TSE.2. When TSE andatypical Scrapie can be excluded, option A; Killing and complete destruction orslaughter for human consumption (SHC) of all animals. Option B: Killing andcomplete destruction of the susceptible animals only. Option C: No mandatorykilling and complete destruction of animals. In Europe, selected male animalswhich have ARR / ARR gene are used in breeding program. As a result of thebreeding programs implemented in Europe; 1108 Scrapie cases reported in 2002decreased to 685 in 2016.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".