Multidimensional positive definite advection transport algorithm (MPDATA): an edge‐based unstructured‐data formulation
Bibliographic record
Abstract
Abstract We report a new development in the area of non‐oscillatory transport methods. We derive, discuss, and test the iterative upwind scheme MPDATA in the Finite Volume framework with the edge‐based data structure and arbitrary hybrid mesh. MPDATA has proven successful in simulations of geophysical flows using single block, structured cuboidal meshes, while employing continuous invertible mappings to accommodate time‐dependent curvilinear domains. Our motivation for the finite‐volume formulation and the choice of unstructured meshes is to facilitate the use of MPDATA schemes for a wider range of applications involving complex geometries and/or inhomogeneous anisotropic flows, where mesh adaptivity is advantageous. Our development preserves the signature benefits of the standard Cartesian‐mesh MPDATA scheme, i.e. the second‐order accuracy, sign‐preservation, and a full multidimensionality free of directional‐splitting errors. Copyright © 2005 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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".