Turkey Lakes Watershed, Ontario, Canada: 40 years of interdisciplinary whole‐ecosystem research
Bibliographic record
Abstract
Abstract The Turkey Lakes Watershed (TLW) study is a federal, interdepartmental study established in 1979 to investigate the effects of acid rain on terrestrial and aquatic ecosystems. The 10.5 km 2 watershed, located in the Eastern Temperate Mixed Forest on the Canadian Shield, has been the site of multidisciplinary studies on biogeochemical and ecological processes conducted across plot to catchment scales. The whole‐ecosystem investigative approach was adopted from the outset and has allowed research to evolve from its original (and continuing) acidification focus to include investigations on the effects of climate change, forest harvesting and other forest ecosystem perturbations. The extensive scientific and support infrastructure allows for collection of a comprehensive data record essential for understanding long‐term environmental trends. Data include atmospheric deposition, meteorology, stream hydrology and chemistry, soil, pore and ground water properties, understory and overstory vegetation, lake and outflow physical and chemical properties, and aquatic macroinvertebrate and fish community composition and abundance. These data have contributed to over 400 published research papers and graduate theses. The watershed has also figured prominently in many continent‐wide comparisons advancing fundamental watershed theory. The knowledge gained at TLW has influenced pollutant emission and natural resource management policies provincially, nationally and internationally.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.023 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".