Strength-Temperature Relationships for First-Year, Second-Year and Multi-Year Sea Ice
Bibliographic record
Abstract
Strength-temperature relationships are presented for four categories of ice: first-year ice (FYI), second-year ice (SYI), young multi-year ice (yMYI) and thick multi-year ice (TkMYI). The equations are based upon the borehole strengths (BHS) measured during 876 tests in 162 boreholes. The strength of every type of sea ice decreases with increasing ice temperature. FYI and SYI are governed by nearly identical BHS-temperature relations for overlapping temperatures in the range -10°C to 0°C, but it is also important to note that SYI can be expected to deteriorate about one month later than FYI. The BHStemperature relations for yMYI and TkMYI are similar over the temperature range -9°C to -2°C. Factors other than ice temperature affect ice strength, so it is to be expected that equations based solely upon ice temperature cannot reproduce the BHS exactly. The BHS was overestimated for 56.8 to 69.4% of tests performed at individual test depths and 61.1 to 72% of the depth-averaged BHS for individual boreholes, depending upon ice category. Cold ice produces the lowest relative errors in strength, and warm porous ice the highest relative errors in strength.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".