Methods of Responsibly Managing End-of-Life Foams and Plastics Containing Flame Retardants: Part I
Bibliographic record
Abstract
Flame retardants (FRs) are added to foams and plastics to comply with flammability standards and test requirements in products for household and industrial uses. When these regulations were implemented, potential health and environmental impacts of FR use were not fully recognized or understood. Extensive research in the past decades reveal that exposure to halogenated FRs, such as those used widely in furniture foam, is associated with and/or causally related to numerous health effects in animals and humans. While many of the toxic FRs have been eliminated and replaced by other FRs, existing products containing toxic or potentially toxic chemical FRs will remain in use for decades, and new products containing these and similar chemicals will permeate the environment. When such products reach the end of their useful life, proper disposal methods are needed to avoid health and ecological risks. To minimize continued human and environmental exposures to hazardous FR chemicals from discarded products, waste management technologies and processes must be improved. This review discusses a wide range of issues associated with all aspects of the use and responsible disposal of wastes containing FRs, and identifies basic and applied research needs in the areas of responsible collection, pretreatment, processing, and management of these wastes.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".