Advancing Mg/Ca Analysis of Coralline Algae as a Climate Proxy by Assessing LA‐ICP‐OES Sampling and Coupled Mg/Ca‐δ<sup>18</sup>O Analysis
Bibliographic record
Abstract
Abstract High‐latitude climate reconstructions are essential for discerning anthropogenic climate change from natural climate variability. Since observational high‐latitude climate records are rare prior to the satellite era, climate proxies such as the coralline algae Clathromorphum compactum are needed to generate these reconstructions. C. compactum is distributed across the northern high latitudes and documents environmental variability in the magnesium‐to‐calcium ratio (Mg/Ca) and δ18O composition of its calcite skeleton. Therefore, paired Mg/Ca and δ18O analyses in C. compactum are a promising new tool for reconstructing historic high‐latitude climate change. Here a new method for C. compactum Mg/Ca analysis, laser ablation‐inductively coupled plasma‐optical emission spectroscopy (LA‐ICP‐OES), was verified through comparisons with parallel Mg/Ca transects using established techniques in a specimen from Labrador, Canada. Next, LA‐ICP‐OES Mg/Ca analysis in two specimens from Nunavut, Canada, was paired with δ18O analyses. While Mg/Ca data across all specimens captured seasonal sea surface temperature (SST) variability, Mg/Ca values differed in replicate transects within skeleton formed at the same time regardless of technique used. This reduces the effectiveness of C. compactum Mg/Ca as a SST proxy on interannual time scales. Mg/Ca values and δ18O composition differed between the two Nunavut specimens, and only one of them documented local SST, sea ice cover, and sea surface salinity. This indicates that climate archive verification is required for each unique coralline algal specimen. In the specimen from Nunavut verified here, paired Mg/Ca and δ18O analyses produced more robust sea ice cover/sea surface salinity reconstructions than δ18O analyses alone, supporting further development of this proxy system.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".