Structural Control of Bedrock Canyon Alignment and Morphology along the Fraser River, British Columbia, Canada
Bibliographic record
Abstract
Bedrock rivers work to incise terrain down to base level. Their geomorphic work is accomplished by the transfer of momentum from flow to particles that strike the bed and walls, or, more effectively, to pluck fracture-bound blocks from the boundary. Through this latter process, bedrock fractures can control bedrock river morphology at the reach scale by dictating local vertical and lateral incision rates. At the watershed scale, regional structure patterns partly control channel alignment by providing fractured rock along discontinuities where incision rates are enhanced. We investigated the structural controls on the alignment of bedrock canyons along the Fraser River, British Columbia, Canada, and controls on the reach-scale morphology of one of its major canyons. We used topographic data and optical imagery derived from multibeam echo-soundings, drones, airborne LiDAR, and satellite sensors. We produced a digital elevation model that includes bedrock walls both above and below the water surface. Our analysis of these data shows that the canyon geometry of the Fraser River is controlled by a combination of large landslides and faults and reveals that epigenetic gorges created by landslides have distinct geometries and morphologies from those canyons associated with faults. Kinematic rock slope analysis of the walls of one major canyon reveals that reach-scale geometry is partly controlled by the orientation of the major joint sets. Vertical and horizontal joints appear to dictate the style of rock erosion and the propensity for abrasion, undercutting, and plucking, and through this control the spatial distribution of constrictions and pools.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".