Freshening of the Alaska Coastal Current recorded by coralline algal Ba/Ca ratios
Bibliographic record
Abstract
[1] Arctic Ocean freshening can exert a controlling influence on global climate, triggering strong feedbacks on ocean-atmospheric processes and affecting the global cycling of the world's oceans. Glacier-fed ocean currents such as the Alaska Coastal Current are important sources of freshwater for the Bering Sea shelf, and may also influence the Arctic Ocean freshwater budget. Instrumental data indicate a multiyear freshening episode of the Alaska Coastal Current in the early 21st century. It is uncertain whether this freshening is part of natural multidecadal climate variability or a unique feature of anthropogenically induced warming. In order to answer this, a better understanding of past variations in the Alaska Coastal Current is needed. However, continuous long-term high-resolution observations of the Alaska Coastal Current have only been available for the last 2 decades. In this study, specimens of the long-lived crustose coralline alga Clathromorphum nereostratum were collected within the pathway of the Alaska Coastal Current and utilized as archives of past temperature and salinity. Results indicate that coralline algal Mg/Ca ratios provide a 60 year record of sea surface temperatures and track changes of the Pacific Decadal Oscillation, a pattern of decadal-to-multidecadal ocean-atmosphere climate variability centered over the North Pacific. Algal Ba/Ca ratios (used as indicators of coastal freshwater runoff) are inversely correlated to instrumentally measured Alaska Coastal Current salinity and record the period of freshening from 2001 to 2006. Similar multiyear freshening events are not evident in the earlier portion of the 60 year Ba/Ca record. This suggests that the 21st century freshening of the Alaska Coastal Current is a unique feature related to increasing glacial melt and precipitation on mainland Alaska.
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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 | 0.000 |
| 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 | 0.000 | 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".