Bibliographic record
Abstract
Abstract Persistent organic pollutants (POPs) comprise a wide range of chemicals, which for the most part have either been intentionally manufactured or created as an unintended consequence of human activities. Some have been used in closed systems (e.g., polychlorinated biphenyls, PCBs, as dielectric fluids), while others are intentionally applied to ecosystem compartments (e.g., organochlorine pesticides). Many POPs are classified as being persistent, bioaccumulative, and toxic: properties that shape their movement and fate in the environment, and dictate their impact on human and animal health. Accidental exposures in humans or widespread ecological impacts in the past led to a variety of national regulations and international treaties, such that some of the more notorious chemical classes are no longer widely used. Such “legacy” POPs contrast the continued use of POPs for which the evidence is less clear and the emergence of new chemical products for which a limited understanding exists (e.g., polybrominated diphenylethers, PBDEs). The extent to which experience from past failures and subsequently developed risk assessment paradigms will protect the biosphere from impacts in the future remains open to debate. Unfortunately, the witnesses are often those far removed from the source of the chemical and represent constituent groups with little influence on regulations, such as the highly POP‐contaminated subsistence‐oriented Inuit people of Arctic Canada, or the killer whales of the NE Pacific Ocean.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.065 | 0.048 |
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".