Reply to the discussion by S. Beltaos on "Ice jam release surges, ice runs, and breaking fronts: field measurements, physical descriptions, and research needs"
Bibliographic record
Abstract
The author would like to thank and acknowledge this contribution of the discusser who has drawn on extensive years of break-up observations, scientific, and engineering re search of very high quality. The author agrees that the use of the term “surge” in the ice jam literature has not been rigorous and that after “the wave has traveled for a long time and become both flatter and slower… the wave is anything but a surge.” The key here is whether or not the wave does become flatter and slower. In many or perhaps even most cases this is true. Certainly, open water theoretical solutions (Ponce and Simons 1977) and field data indicate this. However, under the right conditions, the behavior may be different with an ice cover, since abrupt rises have been triggered by the apparent arrival of a wave from an ice jam release about 100 km upstream (Gerard and Jasek 1990). The question still remains largely unanswered. If a long reach of a river (longer than an open water dynamic wave could theoretically travel) just happens to be at a point of break-up onset, can a dynamic trigger at the upstream end be enough to release enough storage from the channel to maintain its dynamic qualities along the entire reach? The author apologizes for not citing Beltaos (1995, 1997) in the discussion of the concept of “break-up initiating dis charge”. The omission was an oversight and was discovered after the paper had gone to print. The intent was to cite these
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.047 | 0.047 |
| Insufficient payload (model declined to judge) | 0.007 | 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".