Evidence for biomagnification of rubidium in freshwater and marine food webs
Bibliographic record
Abstract
Rubidium (Rb), a rarely studied alkali metal, may be an essential ultra-trace element for humans and other organisms. However, very little information exists in regard to the concentrations and distribution of Rb in freshwater and marine food webs. We measured Rb concentrations in freshwater fish from Lake Erie and two Arctic lakes (Lake Hazen and Resolute Lake) and in seabirds, ringed seals, and invertebrates from the marine Northwater Polynya in Baffin Bay. The alkali analogues of Rb, cesium (Cs), and potassium (K) were also analysed in a subset of fish from Lakes Erie and Hazen. Rb and Cs concentrations and Cs:K ratios in the sampled biota are significantly regressed against δ15N values, indicating biomagnification through the food web in diverse ecosystems. However, there is no relationship between K concentrations and δ15N values, indicating a lack of biomagnification and the presence of homeostatistic mechanisms for this essential trace element. Rb must be included with mercury and Cs as metals that consistently biomagnify in diverse food webs and should be considered in multi-element biomagnification studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".