Decadal variance of summer near-surface temperature maximum in Canada Basin of Arctic Ocean
Bibliographic record
Abstract
In the summer Arctic, bump-like vertical temperature profiles of the upper layer in the Canada Basin suggest a near-surface temperature maximum (NSTM) beneath the mixed layer. This paper concentrates on describing the decadal variance of these NSTMs. Essentially, the temporal evolution of the summer NSTM revealed three decadal phases. The first period is before 2003, when the summer NSTM could rarely be observed except around the marginal of the Canada Basin. The second period is between 2003 and 2015, when the summer NSTM nearly occurred over the whole basin as accelerated decline of summer sea ice. The third period is from 2016 to 2017, when the summer NSTM almost disappeared due to prevailing warm surface water. Furthermore, for the background behind the decadal variance of summer NSTM, linear trends of the September minimum sea ice extent and surface water heat content in the Canada Basin from 2003 to 2017 were –2.75 ± 1.08 × 104 km2yr−1 and 2.29 ± 1.36 MJ m−2yr−1, respectively. According to a previous theory, if we assume that the trend of the summer surface water heat content was only contributed by NSTM, it would cause a decrease in sea ice thickness of approximately 13 cm. The analysis partially explains the reason for sea ice decline in recent years.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".