Global (latitudinal) variation in submarine channel sinuosity: REPLY
Bibliographic record
Abstract
We thank Sylvester et al. (2013) for the opportunity to further consider the nature of, and controls on, sinuosity variation in submarine channels. However, in stating that we propose a Coriolis force (Fc) control on the correlation between peak sinuosity and latitude, and discounted slope and sediment supply, Sylvester et al. misquote us. We concluded “The most probable causative controls on [the] global distribution [of peak sinuosity with latitude] are the Coriolis force… and latitudinal variations in both the nature of flows and sediment type” (Peakall et al., 2012, p. 14). Slope was shown to be a very weak control on global channel sinuosity variation, though it is important in controlling sinuosity in individual channels (Peakall et al., 2012, our figures 1 and 2A).
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.015 | 0.030 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".