Bibliographic record
Abstract
The output of a high-fidelity weather clutter simulation, designed to model low-PRF X-, C-, or S-band phased array radar, is compared with measurements made by three radar systems. The first comparison demonstrates the simulation's ability to replicate real horizon search measurements in terms of various signal properties. The second comparison demonstrates the simulation's ability to generate signals that reflect the vertical dynamic and thermodynamic structure of stratiform precipitation. The third comparison demonstrates the simulation's ability to create weather clutter signals with exotic power spectrum shapes that do exist in nature. In all three cases the simulation output is found to compare well with the real radar measurements. Thus, this simulation is a very good tool for generating realistic weather clutter signals and as such provides a valuable source of data for applications requiring such signals. In addition, this simulation can be used to add controllable weather clutter to existing experimental measurements that may have been affected by weather if it had been present at the time of measurement. This allows the effects of weather clutter to be considered when analysing any experimental data set.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".