Opinions of the Expert Committee for Prions regarding Implementing a Risk Assessment on Beef and Beef Offal Imported to Japan Background
Bibliographic record
Abstract
initiative (self-tasks) as well as those in response to consultations by risk management agencies.- Subjects for self-tasks are nominated at the Expert Committee for Planning, in the light of high potential risk, major public concern and large social impact.- Japan also imports beef and beef offal from countries other than the United States and Canada, where no BSE infected cattle has been detected. Some of these countries were categorised as level III of the Geographical BSE Risk (GBR) by the European Food Safety Agency (EFSA), i.e. it was likely but not confirmed that domestic cattle were (clinically or pre-clinically) infected with the BSE-agent, while some of others have not been assessed by EFSA GBR. Japanese risk management agencies require importers of beef and beef offal to submit an official health certificate confirming the products are not originated from disease cattle, and to refrain from importing specified risk materials (SRM), and inspect them at the quarantine stations. However, potential risk of imported beef and beef offal is not sufficiently clarified partially because BSE prevalence and its countermeasures in those countries are unknown.- The risk assessment on beef and beef offal imported to Japan was requested at the public meetings and others.- These requests seem to be because people feel anxious that the risk of beef and beef
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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 | 0.053 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.015 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".