RADIONUCLIDES AND TRACE METALS IN CANADIAN MOOSE NEAR URANIUM MINES: COMPARISON OF RADIATION DOSES AND FOOD CHAIN TRANSFER WITH CATTLE AND CARIBOU
Bibliographic record
Abstract
Tissues from 45 moose and 4 cattle were collected to assess the health of country foods near uranium mines in northern Saskatchewan. Bone, liver, kidney, muscle and rumen contents were analyzed for uranium, radium-226 (226Ra), lead-210 (210Pb), and polonium-210 (210Po). Cesium-137 (137Cs), potassium-40 (40K), and 27 trace metals were also measured in some tissues. Within the most active mining area, Po in liver and muscle declined significantly with distance from tailings, possibly influenced by nearby natural uranium outcrops. Moose from this area had significantly higher 226Ra, 210Pb, 210Po, and 137Cs in some edible soft tissues vs. one control area. However, soil type and diet may influence concentrations as much as uranium mining activities, given that a) liver levels of uranium, 226Ra, and 210Po were similar to a second positive control area with mineral-rich shale hills and b) 210Po was higher in cattle kidneys than in all moose. Enhanced food chain transfer from rumen contents to liver was found for selenium in the main mining area and for copper, molybdenum and cadmium in moose vs. cattle. Although radiological doses to moose in the main mining area were 2.6 times higher than doses to control moose or cattle, low moose intakes yielded low human doses (0.0068 mSv y(-1)), a mere 0.3% of the dose from intake of caribou (2.4 mSv y(-1)), the dietary staple in the area.
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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 | 0.001 | 0.001 |
| 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".