Bibliographic record
Abstract
ABSTRACT By early 2011, the EU Commission will have published the next edition in one of the most significant legislative acts to have ever impacted the electronics industry. The recast of the EU RoHS Directive (restriction of the use of certain hazardous substances in electrical and electronic equipment) will bring nearly all electrical and electronic products within scope, including medical devices and many other products requiring high reliability. RoHS2 also introduces a number of new conformity obligations. Declaration and authorization of Substances of Very High Concern (SVHC) under the EU REACH regulation is another growing challenge as the number of SVHCs on the Candidate List is expected to rise to over 200 within the next few years. Emerging regulations and voluntary initiatives on carbon footprint will also require electronics to carefully consider product design, material selection, manufacturing and other life cycle stages. This paper presents the new requirements of the EU RoHS2 Directive and the latest updates to the EU REACH regulation for SVHC declaration and authorization. It also discusses several International IEC standards that have been recently published or are in development to assist the electronics industry with compliance to environmental regulations. These standards can help organizations cope with the new regulations and corporate sustainability initiatives in areas including materials declaration, restricted substance controls, environmentally conscious design, material testing, and carbon footprint calculation.
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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 | 0.058 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.015 | 0.024 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.020 | 0.022 |
| Insufficient payload (model declined to judge) | 0.020 | 0.013 |
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".