Retrieval of at-sensor irradiance using Incident Light Sensor ( ILS) *
Bibliographic record
Abstract
A number of aircraft sensors have the facility to measure spectral downwelling irradiance using a sensor mounted on the roof of the aircraft, but these data are rarely used for atmospheric correction.\nPart of the problem is that the attitude of the airborne platform is always changing during flight, even in stable conditions, so that direct use of data from an incident light sensor (ILS) can introduce errors into atmospheric correction methods.\nThe continual motion of the ILS is used here to advantage, as a means to fit a sky radiance distribution model developed by Brunger and Hooper (1993) to data from the Itres Instruments CASI ILS. The inclination of the ILS sensor, due to changing aircraft attitude, is considered as the slope plane in the model. The selected model coefficients correspond to parameterised atmospheric conditions, i.e. clearness index and diffuse ratio. The ILS data corrected by the model are wellmatched\nto variations of irradiance measured at ground level during three flights. The radiance distribution at sensor level is also calculated by the model, and shows the characteristics of the sky conditions at the time of each flight.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 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; both teacher heads agree on what is shown here.
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".