Assessment of Radiometric Data from a Buoy in the St. Lawrence Estuary
Bibliographic record
Abstract
Abstract Fisheries and Oceans Canada maintains a network of scientific buoys in the St. Lawrence estuary and gulf. Among a suite of environmental parameters documented, the in-water upwelling radiance is measured using an ocean color radiometer located underneath the center of the buoy. The shadow effect from the 1.05-m-radius buoy on the measured upwelling radiance is estimated and empirical models to correct for it are proposed. On average, the shading error (i.e., the percent of missing radiance) was and for the 555- and 412-nm channels, respectively. Two analytical models were tested to predict the shading error using measured inherent optical properties, the sun zenith angle, and the fraction of diffuse sky irradiance. Neglecting light scattering led to overestimates of the shading error. In contrast, the bias was removed when the scattering coefficient was accounted for, but the overall error was only barely improved (root-mean-square error ). Empirical relationships based on the uncorrected reflectance ratio measured by the buoy were used to predict both the shading error and the diffuse attenuation of the upwelling radiance, two quantities needed to calculate remote sensing reflectance . Overall, was retrieved with an averaged absolute percent difference ranging from 12% to 20%, which appears adequate for the validation of ocean color data such as the Moderate Resolution Imaging Spectroradiometer (MODIS- Aqua ) and Visible Infrared Imaging Radiometer Suite (VIIRS) products in the optically complex waters of the St. Lawrence estuary.
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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 | 0.000 |
| Open science | 0.001 | 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".