Confluence effects in rivers: Interactions of basin scale, network geometry, and disturbance regimes
Bibliographic record
Abstract
We reviewed 14 studies documenting the effects of tributaries on river morphology at 167 confluences along 730 km of river spanning seven orders of magnitude in drainage area in western United States and Canada. In both humid and semiarid environments the probability of observing significant confluence‐related changes in channel and valley morphology due to tributary influxes of sediment (e.g., changes in gradient, particle size, and terraces, etc.) increased with the size of the tributary relative to the main stem. Effects of confluences on river morphology are conditioned by basin shape and channel network patterns, and they include the nonlinear separation of geomorphically significant confluences in river networks. Other modifying factors include local network geometry and drainage density. Confluence‐related landforms (i.e., fans, bars, terraces, etc.) are predicted to be dominated by older features in headwaters and younger features downstream, a pattern driven by the frequency and magnitude of floods and punctuated sediment supply that scale with watershed size.
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".