Attenuation of in situ UV radiation in Mackenzie Delta lakes with varying dissolved organic matter compositions
Bibliographic record
Abstract
In 2004, ultraviolet‐B (UVB) and ultraviolet‐A (UVA) attenuation were measured in Mackenzie Delta lakes spanning gradients in water renewal rate, dissolved organic carbon (DOC) concentration, and dissolved organic matter (DOM) composition. DOM compositions (ratio of chromophoric DOM (CDOM) to non‐chromophoric DOM) in Delta lakes are complex, evolving seasonally via flooding, dilution, macrophyte production, photobleaching, and bacterial metabolism. Attenuation was more strongly related to CDOM absorption coefficients (a330; UVB r2 = 0.69, p < 0.0001; UVA r2 = 0.58, p < 0.0001) than to DOC concentrations due to variable DOM compositions. Attenuation in one set of lakes was well related (linear models) to a330 and total suspended solids (UVB R2 = 0.80, p < 0.0001; UVA R2 = 0.81, p < 0.0001). When these models were applied to other Delta lakes, however, attenuation of UVB was overestimated in 17 of 19 cases and attenuation of UVA was overestimated in all 18 cases. This bias indicates that models are not transferrable among Delta lakes, and likely cannot be applied in other circumpolar delta lakes with similarly complex DOM compositions. Although attenuation is high in Delta lakes (KdUVB 17.1–33.4 m−1; KdUVA 7.7–19.2 m−1), plankton and photoreactive solutes may be exposed to high levels of ultraviolet radiation (UVR) because Delta lakes are shallow, UVB and UVA penetrate the top 19% and 31% of water columns, respectively, and day lengths are extended during open water. Thus, climate change effects on DOM compositions may significantly alter in situ UVR environments in circumpolar delta lakes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".