Application of the Essential Uses Concept to Substances of Concern - PFAS, 6PPD and Benzene -
Bibliographic record
Abstract
Background: There is growing international recognition of the need for improvements to national chemical management systems for hazardous chemicals.The European Union has recently introduced the concept of 'essential uses' as a new approach to the management hazardous chemicals by limiting their uses.Objectives: This paper examines the concept of essential uses in chemical management and how to apply it through a case study of essential use.This approach is distinct from the current chemical management system, but seeks to improve its potential benefits by effectively restricting or gradually decreasing the use of hazardous substances.Methods: The concept of essential uses was introduced by reviewing the Montreal Protocol on Substances that Deplete the Ozone Layer, Cousins's three essentiality categories applied to PFAS, restriction options assessed in the PFAS restriction proposal under REACH, and the California Safer Consumer Products regulations prioritizing 6PPD in motor vehicle tires.Based on these essential uses concepts for PFAS and 6PPD, uses of benzene were classified in accordance with the essential uses approach for products using benzene in South Korea. Results:The essential use concept is able to manage the restriction and authorization of substances of concern through essential uses and non-essential uses and the feasible substitution of uses and substances.Conclusions: If the concept and methodology of essential uses are clearly established, they can be expected to shift the national chemical management paradigm from regulating substances to limiting uses under the existing substance management 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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".