Lauber and Hager's dam-break wave data for numerical model validation
Bibliographic record
Abstract
Lauber and Hager (1998) have provided a complete set of laboratory data, with both velocity and depth profiles for dam-break flood wave released from a reservoir of finite dimension. At the advancing wave front, the water depth reduces to zero and the velocity peaks. Friction is the dominant effect at the wave front. There is a linear decrease of the velocity from the peak at the wave front toward the back of the dam-break wave. The availability of this data set has provided the opportunity to validate numerical models. The dam-break flood wave is simulated herein using the One-Dimensional Saint-Venant (1DSV) model. A Lagrangian Blocks on Eulerian Mesh (LBEM) method is employed to carry out these calculations. The blocks as the computational elements in the LBEM method produce non-negative depths. Accurate 1DSV model simulation by the LBEM method is possible without the need of a frontal condition for the wet-and-dry interface across the wave front.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".