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Record W4416884757 · doi:10.37665/srdteng22424

How to Cope with the Next Wave in Substance Regulations

2011· article· W4416884757 on OpenAlexaff
Walter Jäger

Bibliographic record

VenueSoldering and Reliability Conferences · 2011
Typearticle
Language
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsDirectiveCarbon footprintConformity assessmentSustainabilityEuropean unionElectronicsLegislatureDeclarationHazardous waste

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.058
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.058
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.088
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0030.001
Science and technology studies0.0050.009
Scholarly communication0.0150.024
Open science0.0050.007
Research integrity0.0200.022
Insufficient payload (model declined to judge)0.0200.013

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.

Opus teacher head0.043
GPT teacher head0.216
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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