Blood concentrations of persistent toxic substances in the indigenous communities of the Russian Arctic
Bibliographic record
Abstract
OBJECTIVES: Investigation was carried out within the framework of the large-scale international project "Persistent Toxic Substances (PTS), Food Security and Indigenous People of the Russian North" under RAIPON/AMAP/GEF aegis. Objectives of the project are to obtain comprehensive information on exposure of indigenous populations to contaminants through food chains (and other sources), and to investigate the possible health effects connected to this exposure. Four regions of Russia are involved in the project: Kola Peninsula (Murmansk oblast), Nenetsk okrug (Pechora river basin), Taimyr Peninsula, Chukotka Peninsula. METHODS: Questionnaire and paired sampling of maternal/cord blood among indigenous women at childbirth (more than 250 persons) as well as among general indigenous population (more than 1,400 persons), additionally breast milk sampling of lactating women (more than 50 persons) in Chukotka was conducted. About 700 blood samples have been analyzed at the Center for Environmental Chemistry, SPA "Typhoon" (Obninsk, Russia), the Regional Center "Monitoring of the Arctic", RCMA (St. Petersburg, Russia), the Norwegian Institute for Air Research, NILU (Tromso, Norway) and at INSPQ (Sainte-Foy, Quebec, Canada). RESULTS AND CONCLUSIONS: On the whole, PTS in human blood of the Russian Arctic natives are similar to those in the coastal areas of Greenland and Canada, and for some POPs such as toxaphenes and mirex, these levels are lower.
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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 | 0.000 | 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 | 0.001 | 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".