Exploring the opening of the Arctic Ocean using lithospheric numerical modelling
Bibliographic record
Abstract
The Circum-Arctic region is a highly active geological region, with repeated opening and destruction of oceans alongside massive intrusive and extrusive volcanic and magmatic events. Although repeated episodes of rifting have been documented in the Arctic region over the past 500 million years and more, a fundamental understanding of the geodynamic processes involved is lacking. For instance, what are the tectonic triggers in the region for the most recent continental breakup via rifting? And, what is the role of earlier deformation events in structural inheritance? A number of different tectonic models describing the opening kinematics of the Arctic Ocean have emerged for post Pangea-times, with many using the opening of the Canada Basin (part of the Amerasia Basin) as a starting point. To study the opening of the Arctic Ocean, methods such as geological mapping, geophysical surveying, geochemical analysis, and plate reconstruction models have been employed to better understand the rifting dynamics of Arctic Pangea, which has produced varying interpretations of how and when the Canada Basin first opened. However, the use of high-performance computing and lithospheric numerical modelling has yet to be fully adopted to investigate Arctic rifting. In this work, we hypothesize that past orogenesis from the assemblage of Arctic Pangea may play a role in subsequent Arctic rifting dynamics and the opening of the Canada Basin. For the first time, we test this hypothesis using lithospheric numerical models with the open-source geodynamic code ASPECT by applying a range of plausible inherited structures to the pre-rift conditions of the Arctic region. Given the uncertainty with the tectonic history of the region, we apply a number of different structural inheritance scenarios to our numerical models – changing lithospheric rheological and rift velocity conditions, as well as simulating different deformation styles from a range of ancient tectonic boundaries in the region. We then critically compare the different rifting styles produced from our suite of models against the data available. Given the limited availability of direct data across this region, for this presentation we welcome community discussion on which key components of continental rifting that may indicate a potential successful modelling of the opening of the Canada Basin. As a rifting community, we want to work toward establishing a set of ‘non-negotiable’ tectonic features to better constrain numerical models of Arctic dynamics that will help push the understanding on tectonic triggers for Arctic plate tectonic processes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".