Experimental validation of the MODTRAN 53 sea surface radiance model using MIRAMER campaign measurements
Bibliographic record
Abstract
Radiometric images taken in mid-wave and long-wave infrared bands are used as a basis for validating a sea surface bidirectional reflectance distribution function (BRDF) being implemented into MODTRAN 5 (Berk et al. [Proc. SPIE5806, 662 (2005)]). The images were obtained during the MIRAMER campaign that took place in May 2008 in the Mediterranean Sea near Toulon, France. When atmosphere radiances are matched at the horizon to remove possible calibration offsets, the implementation of the BRDF in MODTRAN produces good sea surface radiance agreement, usually within 2% and at worst 4% from off-glint azimuthally averaged measurements. Simulations also compare quite favorably to glint measurements. The observed sea radiance deviations between model and measurements are not systematic, and are well within expected experimental uncertainties. This is largely attributed to proper radiative coupling between the surface and the atmosphere implemented using the DISORT multiple scattering algorithm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".