Environmental and seasonal controls on riverine dissolved uranium in the Hudson, James, and Ungava bays region, Canada
Bibliographic record
Abstract
This study documents the spatiotemporal variability of riverine uranium contents and fluxes in rivers discharging into the Hudson, James, and Ungava bays (HJUB). Samples retrieved during a monitoring program of the Koksoak, Great Whale, La Grande, and Nelson rivers were analyzed for dissolved uranium concentration [U] and activity ratio ( 234 U/ 238 U). Field surveys conducted during baseflow and snowmelt in six other rivers of the HJUB basin provided complementary data. It is estimated that altogether, the studied rivers export 3.4 × 10 5 mol/year of U towards the HJUB, with a discharge weighted average ( 234 U/ 238 U) of 1.27. Two main factors appear to control seasonal fluctuations in dissolved U exports from HJUB rivers: snowmelt and anthropogenic flow control. Under natural hydrological regimes, the dilution of U caused by snowmelt does not compensate for the associated increase in discharge, and riverine U fluxes are intensified during springtime. Contrastingly, the timing of riverine U exports is decoupled from hydroclimatic conditions in rivers affected by flow-control structures. Despite the seasonal variations in riverine U contents, the sampling profiles carried along two of the monitored rivers reveal that within the study region, sample locality is at least as important as sampling time for evaluating riverine U fluxes. In addition, a compilation of data from North American rivers reveals that spatial variations in riverine U contents seem to respond to a prominent lithological control, as rivers draining sedimentary rocks (with abundant carbonates) tend to present overall higher U contents and lower ( 234 U/ 238 U) variability than the rivers of the Canadian Shield.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".