The analysis on the SPS measures on food additives notified by WTO numbers during 2010
Bibliographic record
Abstract
During 2010,the members of WTO have notified 203 WTO/SPS measures related food additives,among which China stands first,Canada and EU ran second and third separately.The United States notified few food additive related measures.EU is updating its food additive lists on the regulations.Canada focus on the notifications on enzyme in foodstuff.The Republic of Korea has notified several measures on a large amount of food additives which may have broad impression on the trade of other WTO numbers.Japan focus on the updating of the list of food additives.The Separate Customs Territory of Taiwan,Penghu,Kinmen and Matsu notified the use of food additives on foods in capsule or tablet form.In 2010,China did a good job on the notification of food additive related measures,which are much concerned by other WTO numbers.China should continue to strengthen the notification,in particular,we should also actively study the measures notified by other numbers and submit our comments on them appropriately.The main work should focus on Strengthening the risk assessment on food additives and taking part in the work of Codex Committee on Food Additives.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".