Comparison of seasonal sea-ice thickness change in the Transpolar Drift observed by local ice mass-balance observations and floe-scale EM surveys
Bibliographic record
Abstract
Abstract Local and transect ice-thickness measurements were performed between May and November 2007 on an ice floe in the Transpolar Drift of the Arctic Ocean using an ice mass-balance buoy and electromagnetic induction (EM) sounding. Repeated EM surveys along an originally 2160m long profile including level and deformed ice showed that between June and September modal and mean thicknesses decreased by 0.6 and 0.86m respectively. the modal thickness decrease is in good agreement with the thinning of 0.6m observed by the ice mass-balance buoy at one location on unponded ice during the same period, although the local observations do not capture the different melt rates on level and rough ice. the paper discusses methodological and operational challenges in sustaining both measurements over periods of several months, and concludes that more work needs to be done to better understand their representativeness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".