Mode mixing in sub- and trans-critical flows over an obstacle: When\n should Hawking's predictions be recovered?
Bibliographic record
Abstract
We reexamine the scattering coefficients of shallow water waves blocked by a\nstationary counter current over an obstacle. By considering series of\nbackground flows, we show that the most relevant parameter is $F_{\\rm max}$,\nthe maximal value of the ratio of the flow velocity over the speed of low\nfrequency waves. For subcritical flows, i.e., $F_{\\rm max} < 1$, there is no\nanalogue Killing horizon and the mode amplification is strongly suppressed.\nInstead, when $F_{\\rm max} \\gtrsim 1.1$, the amplification is enhanced at low\nfrequency and the spectrum closely follows Hawking's prediction. We further\nstudy subcritical flows close to that used in the Vancouver experiment. Our\nnumerical analysis suggests that their observation of the "thermal nature of\nthe mode conversion" is due to the relatively steep slope on the upstream side\nand the narrowness of the obstacle.\n
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".