Establishing damage criteria for multi-year ice phase I: thickness and temperature of drifting floes
Bibliographic record
Abstract
Field measurements on multi-year ice in the Canadian Arctic Archipelago are presented, including detailed ice thickness measurements and results of the pilot program to document changes in the temperature of multi-year ice as its drifts through the Arctic. The relevance of monitoring the full thickness temperature of multi-year ice in space and time is that this information can be used subsequently as a proxy for ice thickness and strength. This work, which will span the next four years, is of interest to Transport Canada because it will provide mariners with information to help them rate the damage potential of multi-year ice. It is of interest to the Canadian Ice Service because the results can be incorporated into thermodynamic models and ice drift predictions of multi-year ice. More than 546 m of ice was drilled on four multi-year ice floes during the program. Comparison of thickness measurements from multi-year ice in Nares Strait (2007) and the Canadian Arctic Archipelago (2008) showed that ice upwards of 10 m thick exists in both regions – and, contrary to what one might expect, can be found quite easily. Due to limitations in the amount of auger flight available, the maximum ice thickness measured in Nares Strait during the 2007 season was 16.6 m, although the ice was often considerably thicker. In comparison, the maximum drill hole thickness measured in the Archipelago during the 2008 season was 16.9 m. The average floe thicknesses of the multi-year ice in Nares Strait (2007) ranged from 3.6 to more than 9.6 m, with standard deviations of 0.7 to 3.7 m. The average thickness of the four floes in the Canadian Archipelago (2008) ranged from 7.3 to 9.3 m, with standard deviations from 2.1 to 3.7 m. It should be noted that the crests of the more extreme ice ridges were not sampled during either program. Two months of full thickness temperatures for multi-year floe R02 (10.2 m thick) and three months of temperatures on multi-year floe R05 (10.4 m thick) showed that both floes warmed throughout their full thickness. The rapid warming that occurred at the bottom of Floe R05 during three weeks in August was interpreted as thinning of the ice – the bottom ice thinned by more than one metre in just three weeks. The same cannot be said of Floe R02 because the data terminated prematurely in late July, prior to the onset of bottom ablation. The migration of Floe R02 was documented from 30 May to 20 September, during which time the floe drifted about 1000 km through the Canadian Archipelago. In comparison, Floe R05 circulated in Wellington Channel until 16 August, when the last positional data were obtained from that floe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".