Numerical Simulation of the Wind-Driven Motions in a Two-Layered Lake
Bibliographic record
Abstract
Chapter 2 -LINEAR NUMERICAL MODEL 9Basic assumptions of a general two-layered model 9The volume transport form of the equations of motion and continuity for a two-layer model 12Chapter 3 -NUMERICAL SCHEME 15Description of numerical scheme 15 Input parameters 19Rectangular models of Lake Ontario 20 Chapter 4 -RESULTS OF SIMPLIFIED MODELS 21 Case 1. One-dimensional channel and two-dimensional rectangular basin with flat bottom 21 Case 2. One-dimensional channel and two-dimensional rectangular basin with variable depth in transverse direction only 38 Chapter 5 -TWO-DIMENSIONAL RECTANGULAR BASIN WITH LAKE ONTARIO TOPOGRAPHY 53 A. Models with various types of wind stresses only 53 A. 1. Uniform westerly wind stress 53 A.2. Periodic wind 63 A. 3. Rotating uniform wind over the lake 76 B. Models with various interfacial stress and bottom stress 79 B. 1. Model with coefficient of interfacial stress 5. 0 cm 2 /sec and coefficient of bottom stress 0.0025 79 B. 2. Model with coefficient of interfacial stress 10. 0 cm 2 /sec and coefficient of bottom stress 0.0025 82 B. 3. Model with coefficient of interfacial stress 50.0 cm 2 /sec and coefficient of bottom stress 0. 0025
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".