Haloacetic Acids in Canadian Lake Waters and Precipitation
Bibliographic record
Abstract
Haloacetic acids (HAAs) were measured in lake water and precipitation in distinct geographical areas of Canada with the objective of determining prevailing levels and source regions of these phytotoxins. This included surface water samples from the Great Lakes and four lakes in widely separated geographical areas of Canada. These lakes had levels dependent on the degree of isolation from human activity, with the more isolated lakes having HAA concentration generally of <100 ng/L. Surface water from Lake Superior was sampled at 11 sites during two separate cruises. This lake had HAA levels of <100 ng/L except for dichloroacetic acid which generally was the most abundant of all the HAAs. Two sites from each of the other Great Lakes were sampled, one close to the inflow of the lake and the other close to the outflow. These HAA concentrations were generally 10 times greater than in Lake Superior. For precipitation, the HAA levels were variable (<10−to 2400 ng/L) in daily event samples from seven sites situated across Canada. Five-day back-trajectories indicated that the sources of the air masses govern the types and amounts of HAAs in the precipitation. Urban centers appear to be sources of HAAs, particularly trifluoroacetic acid (TFA). The average daily event precipitation fluxes of TFA were reasonably constant across Canada, except for samples from the station in the Northwest Territories, but those of the chloroacetic acids increased from west to east.
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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 | 0.003 |
| Science and technology studies | 0.002 | 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".