No ion is an island: Multiple ions involved during boron incorporation into CaCO3
Bibliographic record
Abstract
Boron isotope ratios, as measured in marine calcium carbonate, are a proven tracer of past seawater and calcifying fluid pH and thus a powerful tool for the reconstruction of past atmospheric CO2 and monitoring of coral physiology. For such applications, understanding the inorganic baseline upon which foraminiferal vital effects or coral pH upregulation are superimposed should be an important prerequisite. Yet, investigations into boron isotope fractionation in synthetic CaCO3 polymorphs have often reported variable and even conflicting results, implying that we may not fully understand pathways of boron incorporation into calcium carbonate. Here we address this topic with experimental data from calcite and aragonite precipitated across a range of pH in the presence of both Mg and Ca. We confirm the results of previous studies that the boron isotope composition of inorganic aragonite precipitates closely reflects that of aqueous borate ion, but that calcites display a higher degree of scatter, and diverge from the boron isotope composition of borate ion at low pH. We discuss these findings with reference to the simultaneous incorporation of other trace and minor elements, and highlight a number of mechanisms by which crystal growth mechanisms may influence the concentration and isotope composition of boron in CaCO3. In particular, we highlight the potential importance of surface electrostatics in driving variability in published synthetic carbonate datasets. Importantly for palaeo-reconstruction, however, these electrostatic effects are likely to play a much more minor role during natural precipitation of biogenic carbonates.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".