History of Persistent, Bioaccumulative, and Toxic Chemicals
Bibliographic record
Abstract
The history of persistent, bioaccumulative, and toxic chemicals (PBTs) is traced in this chapter from the 1825 synthesis of technical "benzene hexachloride (BHC)" by Faraday to the current international efforts to phase out 12 "persistent, organic pollutants" (POPs) under the auspices of the United Nations Environmental Program (UNEP). In the 1930s, new uses were sought for chlorine, leading to the discovery of a number of chlorinated insecticidal chemicals, including DDT, which earned Müller the Nobel Prize in Medicine for its great success during and following the War to control typhus, malaria, typhoid fever, and cholera. Beginning in the 1960s, however, concerns were identified for the persistence, bioaccumulation, and food chain biomagnification of DDT and other PBTs, and their effects on reproduction in grebes, falcons, and eagles. In addition, these compounds were being detected in geographical locations far from their production and use. PBT properties are found not only in chlorinated pesticides including DDT, but also in halogenated industrial chemicals such as polychlorinated biphenyls. In addition, PBTs, including polychlorinated dibenzo- p -dioxins and dibenzofurans, arise as unintended products of industrial processes or combustion. Although, a large number of chlorinated and brominated compounds have been isolated from natural sources, including marine organisms, it is their production and widespread distribution by anthropogenic sources that is of concern.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".