Inference of optical properties from radiation profiles within melting landfast sea ice
Bibliographic record
Abstract
Vertical in‐ice spectral radiation profiles were measured within melting 1.5‐ to 1.7‐m‐thick landfast sea ice in western Hudson Bay on 25 April 2005. Because the surface ice was subject to extensive melting and refreezing, the sea ice had fractioned into two main types, i.e., areas of more reflective white ice and less reflective blue ice. The shortwave albedo was about 0.69 for white ice and 0.47 for bare blue ice. The corresponding shortwave transmittance through the ice cover was about 0.02 and 0.09, respectively. The inherent optical properties of the sea ice were inferred by tying the input and output of radiative transfer simulations to the radiation profiles and the ice physical properties, as well as to the irradiance measurements above and below the ice cover. To explain observed spectral albedo and transmittance simultaneously, the ice/snow above the interior ice was divided into three layers on the basis of the following observations: snow (white ice) or a thin soot containing layer (blue ice), drained ice above and saturated ice below the waterline. Similarly, the bottom portion was divided on the basis of the presence of a living ice algae layer adjacent to the seawater interface and a layer extending 30 cm above the bottom containing mostly detrital matter. The interior of the ice, i.e., roughly 20–40 cm from boundaries, was well‐represented by a single layer of pure sea ice as the radiation field was nearly asymptotic and the absorption spectra showed little evidence of impurities. Representative values for the scattering coefficient ranged 600–800 m−1, with a Henyey‐Greenstein asymmetry parameter of 0.995. Observations within white ice suggest that about 40% of the energy responsible of the internal melting was provided directly by shortwave radiation, while the rest is due to heat conduction.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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 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".