Bibliographic record
Abstract
I analyzed the 21 year dynamics of dissolved organic carbon (DOC) in 55 lakes in five sites across Eastern Canada in relation to regional and global variables.Regional variables included total solar radiation (TSR), precipitation (PPTN), air temperature (T) and sulfate deposition (SO 4 ).Global variables included the Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO) 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 between sites, except for Kejimkujik and Yarmouth which were only 80 km apart from each other.This suggested that the variation of the long-term DOC pattern was in response to the temporal pattern of regional variables, and it supports the recent understanding that regional factors have a strong influence on many lake properties.Significant long-term trends in DOC were not evident except at the Experimental Lakes Area (ELA), where an increase in DOC was observed together with a decrease in summer TSR and an increase in summer precipitation.Annual mean air temperature has increased at the Nova Scotia and Turkey lakes sites over the study period.The relationship between the long-term pattern in DOC with the regional and global variables was analyzed for each study site to determine the key variables that could best explain the variation in the long-term pattern in DOC.TSR and PPTN were important independent variables across all sites, except for the Turkey Lakes Watershed site (TLW).Summer TSR (annual TSR for Kejimkujik and Yarmouth) had a negative relationship, while summer precipitation had a positive relationship with the long-term DOC pattern for all sites except TLW.TSR and PPTN explained 78%, 49% and 84% of I would like to acknowledge and thank my supervisor Dr. Jeffrey Hudson for his insights, support, encouragement, and guidance, which have greatly improved this thesis and my abilities as a researcher.
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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 | 0.001 |
| 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".