Physical and electrical characteristics of snow on sea ice: Implications for forward scattering model development
Bibliographic record
Abstract
The authors quantify the vertical and seasonal characteristics of the geophysical and electrical properties of snow covers on landfast first-year and multiyear sea ice. Snow grain size, density, salinity, temperature and wetness were measured; the volume fractions of air, ice, brine, and the complex dielectric constant of the snow and sea ice were modelled over a cm vertical resolution spanning the seasonal periods from April to June. First-year sea ice snow covers (FYI'92 and FYI'93) showed that over the vertical dimension all variables depict a multilayer system. Deposition of a new snow cover (FYI'92) significantly altered the physical characteristics of the snow volume but not the dielectric properties. The basic vertical patterns observed in FYI'92 were also observed in FYI'93, except for the influence of the new snow layer of FYI'92. The pattern of physical and electrical characteristics for a multiyear sea ice snow cover were statistically different than an equivalent first-year ice case. Modelling of the snow grain area size characteristics can be done using a family of chi-square distributions with varying degrees of freedom.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".