The Mantle Seismic Structure below Canada and Alaska Constrained by a New Absolute P-wavespeed Tomographic Model
Bibliographic record
Abstract
Mapping absolute P-wavespeeds in the Canadian and Alaskan mantle will further our understanding of its present-day state and evolution. S-wavespeeds are relatively well constrained, especially across Canada, but are primarily sensitive to temperature while complimentary P-wavespeed constraints provide better sensitivity to compositional variations. One technical issue concerns the difficulties in extracting absolute arrival-time measurements from often-noisy data recorded by temporary seismograph networks. Such processing is required to ensure that regional Canadian datasets are compatible with supplementary continental and global datasets provided by global pick databases. To address this, we utilize the Absolute Arrival-time Recovery Method (Boyce et al., 2017). We extract over 180,000 new absolute arrival-time residuals from seismograph stations across Canada and Alaska that include both land and ocean bottom seismometers. We combine these data with the latest USArray P-wave arrival-time data from the contiguous US and Alaska. Using an adaptively parameterised least-squares tomographic inversion we develop a new absolute P-wavespeed model, with focus on Canada and Alaska (CAP21). Initial results suggest fast wavespeeds characterise the upper mantle beneath eastern and northern Canada. A sharp transition between the slow wavespeeds below the North American Cordillera and the fast wavespeeds of the stable continental interior appears to follow the Cordilleran Deformation Front (CDF) in southwest Canada. Slow wavespeeds below the Mackenzie Mountains may extend further inland of the CDF in northwest Canada. In Alaska, CAP21 illuminates both lithospheric structure and the along strike morphology of the subducting slab. The newly compiled data may also improve resolution of subducted slab remnants in the mid-mantle below the North American continent, crucial to help constrain the formation of the Alaskan peninsular at ≥50Ma.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".