Properties of level landfast ice and hummocked ice near Nain, Labrador
Bibliographic record
Abstract
This report discusses property measurements that were made on level first-year sea ice near Nain, from early February to mid May 2004. Ice thickness ranged from 0.41 to 0.65 m in February, and 0.89 to 1.20 m in mid-May. The highest borehole strengths were measured in March, when the ice was coldest. Results showed that, in general, ice strength decreased more rapidly towards the top and bottom surfaces than in the ice interior. The strength reduction was due to ice decay, clear evidence of which was provided by the deteriorated state of the extracted cores, and changes in the temperature and salinity of the ice. Measurements are also given for hummocked ice sites that were sampled in a quasi-stable area of landfast ice, in April. The ice surface relief increased, as did the ice and snow thickness, as the hummock field was penetrated. Ice thickness at the first site ranged from 0.99 to 1.17 m, whereas ice at the fourth site ranged from 1.14 to 2.20 m thick. The hummocked ice was isothermal at near melting temperatures throughout its full thickness. The ice salinity was minimal in the top ice, ranged from 4 to 5‰ in the ice interior, and was upwards of 8‰ towards the bottom ice. The highest borehole strength was measured in the interior of the ice. On average, the hummocked was thicker and stronger than the level landfast ice (for the same time of year).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".