Glacial hydro-isostatic adjustment at mid-ocean ridges
Bibliographic record
Abstract
SUMMARY Recent studies have suggested a link between ice age sea level fluctuations and variations in magma production and crustal faulting along mid-ocean ridges based on the detection of Milankovitch cycle frequencies in topography off several ridges. These fluctuations have also been connected to variability in hydrothermal metal fluxes near ridges. Ice age sea level calculations have shown that the sea level change across glacial cycles will be characterized by significant geographic variability, that is, departures from eustasy, due to the gravitational, deformation and rotational effects of the glacial isostatic adjustment (GIA) process. Using a state-of-the-art GIA simulation that incorporates 3-D variations in Earth viscoelastic structure, including plate boundaries and updated constraints on the magnitude and geometry of ice mass fluctuations, we predict global sea level changes from last glacial maximum (LGM, 26 ka) to present and from the penultimate glacial maximum (143 ka) to the last interglacial (128 ka). We focus on the results along three ridges: the Mid-Atlantic Ridge, Juan de Fuca Ridge and East Pacific Rise, which are examples of slow, intermediate and fast spreading ridges, respectively. Sea level change across the Mid-Atlantic Ridge shows the greatest variability, ranging from a sea level fall greater than 200 m in Iceland to a maximum rise of ∼150 m in the South Atlantic, with significant non-monotonicity north of the Equator as the ridge weaves across the field of sea level changes. We also calculate changes in crustal normal stress from LGM to present-day across the Mid-Atlantic and Juan de Fuca Ridges and the East Pacific Rise. These results indicate that the contribution from ice mass changes to the crustal stress field can be significant well away from the location of ancient ice complexes. We conclude that any exploration of the hypothesized links to magma production and crustal faulting must consider both ocean and ice loading effects and, more generally, the profound geographic variability of the GIA process.
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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) | 0.013 | 0.006 |
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; both teacher heads agree on what is shown here.
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".