Recycling Technology and Supervision Strategies of Food Contact PET Bottle
Bibliographic record
Abstract
According to its excellent properties, polyethylene terephthalate (PET) is widely used as food containers in mineral water, soft drinks, beers, etc., resulting in a huge waste of PET bottles which increases the environmental burden. With the development of the recycling technology of PET bottles, the discarded PET bottles after consumption have been reused as food containers in many countries successfully. This paper is mainly focused on the new developments of chemical and physical PET recycling technology and its application in enterprises and outlines regulations in the United States, Canada, the European Union, Britain, Japan, South Korea and other countries. The relevant laws and regulations of PET recycling as food containers in our country have also been reviewed. The purpose of this paper is to provide reference opinions on recycling PET to produce food contact materials in China, including promoting waste classification management, improving the risk assessment systems, and formulating relevant national food safety standards.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".