A statistical evaluation of water quality trends in selected water bodies of Newfoundland and Labrador
Bibliographic record
Abstract
Using water quality data collected since 1986, as part of the Canada–Newfoundland Water Quality Monitoring Agreement, 36 different water quality variables from 65 different water quality monitoring sites were examined for change over time. Moving averages, the Student's t test statistic, and Spearman's rank correlation coefficient were used. Throughout the province, turbidity and colour were generally displaying deteriorating trends, while conductivity, copper, lead, and mercury were consistently displaying improving trends. There was a notable deteriorating trend in nitrate and nitrite and nitrogen in select river basins, and an improving trend in phosphorous in more developed basins. Even in pristine watersheds, change was often observed in metals, major ions, turbidity, and colour. An examination of land and water use activities ongoing in each watershed allowed identification of likely localized causes and (or) factors contributing to observed water quality trends. In many cases trend-causing factors appeared to be more global in nature and most trends could be explained by an upward trend in river flows during the period analyzed. Key words: water quality, Newfoundland, Labrador, trends, Spearman, land use, statistics, streamflow.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| 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".