Imprint of the Pacific decadal oscillation on the Western Canadian Arctic climate.
Bibliographic record
Abstract
It is well established that the Arctic strongly influences the global climate through positive feedback processes, one of \nthe most effective being the decrease in sea-ice extent (Cohen et al. 2014, Screen and Simmonds 2010). Understanding \nthe internal mechanisms forcing the climate variability of this region is thus a prerequisite to better forecast future global \nclimate variations. Here, sedimentological evidence from an annually laminated record highlights that the Pacific \nDecadal Oscillation (PDO) has been a persistent regulator of the regional climate in the Western Canadian Arctic since \nthe past 700 years. Annual varve thickness from East Lake at Cape Bounty, Melville Island, is negatively correlated to \nthe PDO indexes (Mantua et al. 1997, MacDonald and Case 2005, Gedalof and Smith 2001, D’Arrigo et al. 2001) \nthroughout most of the last 700 years, suggesting drier conditions during high PDO phases, and vice-versa. This is in \nagreement with known regional teleconnections whereby PDO indexes are negatively and positively correlated to pre \ncipitation and mean sea level pressure, respectively. These climate anomalies projecting onto the PDO- (NPI+) phase are \nkey factors in enhancing evaporation and subsequent precipitation in this region. As projected sea-ice loss will contribute \nto enhanced future warming in the Arctic, future negative phases of the PDO (or NPI+) will likely ast as amplifiers of \nthis positive feedback.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".