Vol 2, no. 2
Bibliographic record
Abstract
As Ottawa River contamination is historical and resides in sediment, ecological risk and trophic transfer depend on linkages between sediment and biota. One of the ways in which this linkage is quantified is through the use of the biota sediment accumulation factor (BSAF). In this study, we present the first field estimates of BSAF for a number of radionuclides. The strongest and most consistent BSAFs were those for 137 Cs in deposit feeding taxa, suggesting that sediment concentrations rather than dissolved concentrations drive uptake. For crayfish and unionid bivalves that do not feed on sediment, biota radionuclide concentrations were not related to sediment concentrations, but rather reflected concentrations in water. BSAFs would not be appropriate for these non-deposit feeding biota. BSAFs for 137 Cs were not significantly different among deposit feeding taxa, suggesting similar processes for ingestion, assimilation and elimination. These data also show that the concentration factor approach used for guidance would have led to spurious results in this study for deposit feeding benthic invertebrates. Concentrations of 137 Cs in Hexagenia downstream of the CRL process outfall range by about 2-orders of magnitude, in comparison to relatively uniform water concentrations. The concentration factor approach would have predicted a single value downstream of CRL, underestimating exposure to Hexagenia by almost 2-orders of magnitude at sites close the CRL process outfall.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.109 | 0.040 |
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".