Long‐term patterns of dissolved organic carbon in lakes across eastern Canada: Evidence of a pronounced climate effect
Bibliographic record
Abstract
We analyzed the 21‐yr dynamics of dissolved organic carbon (DOC) in 55 lakes during ice‐free periods in five regions across eastern Canada in relation to total solar radiation (TSR), precipitation, air temperature, sulfate deposition (SO4), Southern Oscillation Index (SOI), North Atlantic Oscillation, and Pacific Decadal Oscillation (PDO). A synchronous pattern in DOC was found among lakes within each region; however, a synchronous pattern in DOC was not found among regions, except for Kejimkujik and Yarmouth. Long‐term trends of increasing or decreasing DOC concentration were not evident except at the Experimental Lakes Area (ELA), where an increase in DOC correlated with a decrease in summer TSR and an increase in summer precipitation. Annual mean temperature increased at the Nova Scotia and Turkey Lakes Watershed regions (TLW) over the study period, but there was no corresponding change in DOC. TSR and precipitation were important explanatory variables across all regions, except for the TLW. Summer TSR, or annual TSR, had a negative relationship, while summer precipitation had a positive relationship with the temporal DOC pattern in all regions except TLW. TSR and precipitation explained 78%, 49%, and 84% of the variation in the long‐term DOC patterns at Dorset, ELA, and Nova Scotia (NS) regions, respectively. In contrast, the long‐term pattern in DOC at TLW was only weakly related to SOI and PDO.
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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 | 0.001 | 0.000 |
| 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".