Morphometric controls and geomorphic responses on fans in the Southern Alps, New Zealand
Bibliographic record
Abstract
Abstract Morphometric variables associated with 41 debris‐flow and 18 fluvial fans and their basins in the Southern Alps of New Zealand are examined. The results show statistically significant differences in the area, maximum elevation, relief and ruggedness (Melton's R) of the basin and the area, gradient, and apex and toe elevations of the fan between debris‐flow and fluvial sites. Concavity of the fan longitudinal profile also differs between the two fan types, although this could not be tested statistically. Most of these morphometric differences reflect differences in processes and environmental controls on them. Discriminant analysis indicates that basin area and fan gradient best differentiate the two fan types by process. Moderately strong correlations exist, on both debris‐flow and fluvial fans, between basin area or Melton's R and fan area. Correlations between basin area or Melton's R and fan gradient are generally weaker. The results of this study also indicate that on debris‐flow‐prone fans the fan gradient and basin Melton's R have lower thresholds which overlap little with upper thresholds associated with basins where only streamflow reaches the fan. These thresholds may therefore have value in preliminary morphometric assessments of debris‐flow hazard on fans in the Southern Alps. Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".