Exposure of Russian Phenoxy Herbicide Producers to Dioxins
Bibliographic record
Abstract
Russian workers who manufactured phenoxy herbicides and related compounds in the 1960s in the city of Ufa, Bashkortostan, a republic of the former Soviet Union, were studied for exposure to polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans. Sixty whole blood samples were drawn in September 1992 and analyzed by gas chromatography-mass spectrometry. Thirty-four workers who manufactured the herbicide 2,4,5-trichlorophenoxyacetic acid (2,4,5-T) had median blood lipid 2,3,7,8-tetrachlorodibenzo-p-diozin (TCDD) concentrations of 166 ng per kg (parts per trillion) and 1,2,3,7,8-pentachloro-p-dioxin (PnCDD) levels of 52 parts per trillion with several TCDD values greater than 500 ng/kg. These 1992 values are 10 to 30 times greater than contemporary normal or background blood levels from the Baskortostan region of Russia and were at least 10-fold higher 25 years earlier in the late 1960s. Six workers who produced the herbicide 2,4-dichlorophenoxyacetic acid also had elevated levels in 1992, with 1,2,3,7,8-PnCDD blood lipid levels higher than 2,3,7,8-TCDD. Even children of some of the workers and factory administrative personnel had blood levels of TCDD higher than most general population groups from other parts of Russia or from other countries. The patterns of the PCDDs and dibenzofurans (as defined by the specific congeners and their relative amounts) were distinctive for the type of chemical produced, with notable contributions to the TCDD toxic equivalents from the 2,3,7,8-TCDD and 1,2,3,7,8-PnCDD congeners. No correlation was found between chloracne status in 1965 to 1967 and TCDD or toxic equivalent blood lipid concentrations in 1992. These Russian phenoxy herbicide and related chemical producers have some of the highest occupational exposure to dioxins of any cohort studied to date and seem to be unique with respect to the presence of appreciable amounts of 1,2,3,7,8-PnCDD.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".