Heavy silicon isotopic composition of silicic acid and biogenic silica in Arctic waters over the Beaufort shelf and the Canada Basin
Bibliographic record
Abstract
Abstract The silicon isotopic composition of silicic acid (δ 30 Si(OH) 4 ) and biogenic silica (δ 30 Si‐bSiO 2 ) were measured for the first time in marine Arctic waters from the Mackenzie River delta to the deep Canada Basin in the late summer of 2009. In the upper 100 m of the water column, δ 30 Si(OH) 4 signals (+1.82‰ to +3.08‰) were negatively correlated with the relative contribution of Mackenzie River water. The biogenic Si isotope fractionation factor estimated using an open system model, 30 ε = −0.97 ± 0.17‰, agrees well with laboratory and global‐ocean estimates. Nevertheless, the δ 30 Si dynamics of this region may be better represented by closed system isotope models that yield lower values of 30 ε , between −0.33‰ and −0.41‰, depending on how the contribution of sea‐ice diatoms is incorporated. In the upper 400 m, δ 30 Si‐bSiO 2 values were among the heaviest ever measured in marine suspended bSiO 2 (+2.03‰ to +3.51‰). A positive correlation between δ 30 Si‐bSiO 2 and sea‐ice cover implies that heavy signals can result from isotopically heavy sea‐ice diatoms introduced to pelagic assemblages. Below the surface bSiO 2 production zone, the δ 30 Si(OH) 4 distribution followed that of major water masses. Vertical δ 30 Si(OH) 4 profiles showed a minimum (average of +1.84 ± 0.10‰) in the upper halocline (125–200 m) composed of modified Pacific water and heavier average values (+2.04 ± 0.11‰) in Atlantic water (300–500 m deep). In the Canada Basin Deep Water (below 2000 m), δ 30 Si(OH) 4 averaged +1.88 ± 0.12‰, which represents the most positive value ever measured anywhere in the deep ocean. Since most Si(OH) 4 enters the Arctic from shallow depths in the Atlantic Ocean, heavy deep Arctic δ 30 Si(OH) 4 signals likely reflect the influx of relatively heavy intermediate Atlantic waters. A box model simulation of the global marine δ 30 Si(OH) 4 distribution successfully reproduced the observed patterns, with the δ 30 Si(OH) 4 of the simulated deep Arctic Ocean being the heaviest of all deep‐ocean basins.
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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 | 0.000 | 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".