Response of river channel morphology to urbanization: the case of Highland Creek, Toronto, Ontario, 1954-2005
Bibliographic record
Abstract
Current studies of urban channel form attempt to understand channel response to major changes in prevailing controlling conditions, mainly discharge. But very few studies actually track channel adjustment over the course of urbanization, ignoring the complexity of channel adjustment to other factors such as large floods and/or engineering. Seldom have these changes been analyzed in terms of expected adjustment from regime theory and the actual processes o f adjustment. Highland Creek in Toronto, Ontario has undergone a rapid transformation from mainly rural to almost completely urban land-use (85% of the drainage area) from 1954 to 2005. It has had a pronounced hydrological response with peak flows reaching up to nine times the pre-urban maximum. Channel form was measured from a series of 5 sets of air photos (1954, 1965, 1978, 2002, and 2005) encompassing the entire development period. The results of this analysis in general indicate that the Creek has become wider and sinuosity has decreased, but variability exists temporally and spatially. Comparison with predicted channel widths using regime theory shows that much of the channel length has ‘under-adjusted’ compared to expectations. It is apparent that this resulted from extensive channel engineering, preventing channel adjustment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".