Probable changes in lake chemistry in Canada’s Atlantic Provinces under proposed North American emission reductions
Bibliographic record
Abstract
Abstract. Atlantic Canada, located in the extreme north-eastern portion of North America, receives acid precipitation from all major acid emission sources on the eastern part of the continent. The region was glaciated and has thin soils over a generally poorly acid buffering bedrock. Because of regional topography, large groupings of lakes occur in a number of regions. Environment Canada and the Government of New Brunswick have operated lake sampling networks in trend detection studies and have concentrated their work on these lake groupings. The MAGIC model has been applied to these lakes and their catchments to see: a) what initial water chemistry conditions existed before acidification began, b) what the chemistry was like during the worst of regional acid deposition, and c) what it would be like under deposition conditions predicted for new Canadian and US emission reduction proposals. While pH, sulphate, acid neutralisation capacity (ANC) and the sum of the base cations (SBC) of all lakes have been significantly affected by acid deposition, water chemistry conditions are now considerably better than they were in 1975, at the worst of the deposition. However, a 50% reduction in acid deposition from Year 2000 deposition amounts will not return water chemistry to original conditions in most of the region. Keywords: Atlantic Canada, monitoring networks, acidification, predictions, MAGIC
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".