Glacial erosion, evolution of river long profiles, and the organization of process domains in mountain drainage basins of coastal British Columbia
Bibliographic record
Abstract
In glaciated British Columbia, Canada, Quaternary climate changes are responsible for profound spatial reorganization of Earth surface processes. These changes have left a landscape characterized by topographic anisotropy associated with a hierarchy of glacial troughs. The evolution of glaciated landscapes is examined by analyzing the structure of geomorphic process domains and channel long profiles. To identify process domains we use channel surveys and GIS analysis to construct slope‐area transects of the channel network. This analysis reveals generalized process‐form disequilibrium with a mismatch between topographic signatures and currently active geomorphic process domains. At the landscape scale of “source” colluvial channels (contributing area <1 km2), the glacial/paraglacial signature commonly overrides that produced by contemporary debris flows. Along the axis of former ice flows, relict glacial cirques introduce a “hanging” fluvial domain at contributing areas as small as 8 × 10−2 km2 and produce complex channel long profiles similar to those observed for rivers responding to tectonic forcing. Slope‐area relations typical of unglaciated equilibrium environments do not apply here. The concept of process domains appears to hold, however, some major glacially forced modifications in the alluvial‐colluvial transition are observed and the definition of a depositional colluvial subdomain is proposed. Comparison between field‐ and GIS‐measured slopes reveals that GIS‐associated error is not uniform between process domains, and that GIS‐based plots do not successfully discriminate field‐based process domains. The combination of glacial and post‐glacial fingerprints and the effects of ongoing Earth surface processes generate a complex landscape whose glacial signatures may persist until the onset of the next ice age.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 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".