Modeling optical refraction and turbulence effects within the MSBL (marine surface boundary layer)
Bibliographic record
Abstract
PIRAM is a french bulk model that computes, within the MSBL, vertical refractivity profiles and refractivity gradients calculated for each optical transmission window as well as for radar bands. PIRAM also computes the C<SUB>n</SUB><SUP>2</SUP> vertical profiles. Under unstable situations, subrefraction occurs and reduces the optical horizon. Near the horizon an intervisibility zone may be observed: any source (target) located in this zone will be seen by an EO sensor under two distinct apparent elevation angles. We developed, a few years ago, a simple ray-tracing algorithm using PIRAM refractivity outputs, to compute optical horizons and intervisibility ranges for a given atmospheric situation. More recently, we have added new capabilities to our ray-tracing program; now, it also computes the refractance parameter and the optical path between a given optical source or target and the considered EO sensor. Atmospheric turbulence effects are quantified by several parameters such as the scintillation variance, the atmospheric coherence length or the standard deviation of the angular displacement. All these parameters are computed by taking into account the exact optical path and the complete C<SUB>n</SUB><SUP>2</SUP> vertical profile. Our first comparisons with the values provided by the Canadian IRBLEM software lead to promising results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".