A 6000-year record of interaction between Hamilton Harbour and Lake Ontario: quantitative assessment of recent hydrologic disturbance using 13C in lake sediment cellulose
Bibliographic record
Abstract
Abstract Hamilton Harbour, a heavily urbanized and polluted embayment, has been selected for environmental remedy by an International Joint Commission. Ecosystem restoration efforts, however, require an understanding of harbour water balance and in particular the influence of recently enhanced exchange with the more dilute waters of Lake Ontario via the Burlington Canal. Here we provide a 6000-year quantitative reconstruction of hydrologic communication between Hamilton Harbour and Lake Ontario, based on the carbon isotope composition in the cellulose of the lake sediment, as a tracer of dissolved inorganic carbon. Results indicate that excavation of the canal has led to mixing levels 30–100% greater than the natural hydrologic state, conditions comparable to the Nipissing Flood when Upper Great Lakes drainage was diverted through Lakes Erie and Ontario roughly 5000 years ago. The effects of elevated exchange are clearly displayed by abrupt attenuation of anthropogenically driven eutrophication in the uppermost sediments from Hamilton Harbour. Thus, restoring the harbour water balance to predisturbance status would generate unfavourable environmental conditions in the harbour unless the effluent discharge to the harbour is eliminated entirely.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".