Modification of the LTHIA GIS model to assess the water quantity and quality of Canadian Great Lakes watershed
Bibliographic record
Abstract
In this study, the LTHIA model was used to analyze the surface runoff and two Non-Point Source pollution – total suspended solids (TSS) and total phosphorus (TP) of the Canadian Great Lakes watershed. The temporal analysis showed the highest runoff, TSS and TP in the Northern Lake Erie sub-watershed in 1954 whereas the lowest was observed in the Northwestern Lake Superior sub-watershed in 1952. The spatial analysis showed higher runoff, TSS and TP in the Eastern Lake Huron and Northern Lake Erie sub-watersheds. The decadal analysis revealed higher runoff, TSS and TP in 1980-90, 1990-99 and 2000-09. The climate change analysis revealed that more variation in the runoff, TSS and TP were projected in mid-century (2035-64) as compared to end-century (2070-99). Finally, it has been shown that LTHIA model can successfully be used to simulate both water quantity and quality related processes as well as climate change effect.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".