Patterns of hydrogen peroxide among lakes of the Mackenzie Delta, western Canadian Arctic
Bibliographic record
Abstract
Dissolved organic carbon (DOC) in Mackenzie Delta lakes varies in composition and concentration, ranging from low concentrations and high colour in frequently flooded lakes to high concentrations in clear lakes that are infrequently flooded. DOC is a precursor to the photochemical production of hydrogen peroxide (H2O2) in lake waters. Here we assessed the patterns of H2O2using three approaches: (i) H2O2levels were tracked in 40 lakes during the open water season from the Arctic summer solstice (24 h sunlight) to late summer; (ii) diurnal dynamics of in situ H2O2were tracked in a pair of lakes with contrasting DOC regimes (coloured vs. noncoloured DOC); and (iii) buildup of H2O2was tracked in experimental microcosms of lake water exposed to manipulated UV levels. H2O2levels were highest at the solstice and in intermittently flooded lakes. During 24 h daylight, lakes with contrasting DOC regimes showed cumulative build up of H2O2during multiple cloudless days. Cumulatively, H2O2was highest in the Delta lake with a higher DOC concentration and low in colour. H2O2buildup in lake water shielded from UVB exposure was not significantly lower from microcosms under full sunlight. UVA was the most important in coloured DOC photobleaching and H2O2production.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".