Response of transient rock uplift and base level knickpoints to erosional efficiency contrasts in bedrock streams
Bibliographic record
Abstract
Abstract Knickpoints in bedrock streams are often interpreted as transient features generated by a change in boundary conditions. It is typically assumed that knickpoints propagate upstream with constant vertical velocities, though this relies on a stream being in erosional steady state (erosion rate equals rock uplift rate) prior to the knickpoint's formation. Recent modeling and field studies suggest that along‐stream contrasts in rock erodibility perturb streams from erosional steady state. To evaluate how contrasts in rock erodibility might impact knickpoint interpretations, we test parameter space (rock erodibility, rock contact dip angle, change in rock uplift rate) in a one‐dimensional (1D) bedrock stream model that has variable rock erodibility and produces a knickpoint with a sudden change in rock uplift rate. Upstream of a rock contact, the vertical velocity of a knickpoint generated by a change in rock uplift rate is strongly correlated with how the rock contact has previously perturbed erosion rates. These knickpoints increase vertical velocity upon propagating upstream of a hard over soft contact and decrease vertical velocity upon propagating upstream of a soft over hard contact. However, interactions with other transient perturbations produced by rock contacts make for nuances in knickpoint behavior. Rock contacts also influence the geometry of knickpoints, which can become particularly difficult to identify upstream of soft over hard rock contacts. Using our simulations, we demonstrate how a contact's along‐stream horizontal migration rate and cross‐contact change in rock strength control how much an upstream reach is perturbed from erosional steady state. When simulations include multiple contacts, the knickpoint is particularly prone to colliding with other transient perturbations and can even disappear altogether if rock contact dips are sufficiently shallow. Caution should be taken when analyzing stream profiles in areas with significant changes in rock strength, especially when rock contact dip angles are near the stream's slope.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".