Glacially induced organization of channel‐reach morphology in mountain streams
Bibliographic record
Abstract
We examine the spatial distribution of channel‐reach morphologies in formerly glaciated mountain drainage basins of coastal British Columbia, Canada. Using field‐ and geographic information systems‐derived data, we show that the local channel slope and the degree of colluvial‐alluvial coupling imposed by the glacial valley morphology dictate the spatial organization of channel types. In particular, the complex, glacially induced channel long profile produces characteristic sequences of channel reaches that depart from the downstream succession (colluvial/boulder‐cascade/step‐pool/rapids/riffle‐pool) distinctive of simple unglaciated mountain streams. Typically, the presence of one hanging valley in the river long profile produces and separates two full successions of channel types: a headmost one characterized by an ephemeral/seasonal hydrologic regime and a downstream one, where water runoff is perennial. We document that channel types are well separated in plots of slope versus shear stress, area versus shear stress, and slope versus relative roughness. In agreement with these outcomes, multivariate discriminant analyses coupled with principal component analysis of 98 study reaches yield a highly successful channel‐type classification when slope, shear stress, and relative roughness are considered. Success rates, depending on whether or not boulder‐cascade reaches are pooled together with step‐pools, are 88% and 75%, respectively. Previous work in unglaciated settings has suggested that mountain channels have distinct bed morphology states that vary primarily with slope; our study reveals that even in formerly glaciated valleys, where slope is largely inherited from glacial times, these distinct bed states exist and vary (mostly) with slope, adding considerable strength to this empirical knowledge.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".