Moho Variations across the Northern Canadian Cordillera
Bibliographic record
Abstract
Abstract Moho morphology in orogens provides important constraints on the rheology and density structure of the crust and underlying mantle. Previous studies of Moho geometry in the northern Canadian Cordillera (NCC) using very sparse seismic data have indicated a flat and shallow (∼30–35 km) Moho, despite an average elevation of >1000 m above sea level attributable to increased thermal buoyancy and lower crustal flow due to elevated temperatures. We estimate Moho depth using receiver functions from an expanded dataset incorporating 173 past and recently deployed broadband seismic stations, including the EarthScope Transportable Array, Mackenzie Mountains transect, and other recent deployments. We determine Moho depths in the range 27–43 km, with mean and standard deviations of 33.0 and 3.0 km, respectively, and note thickened crust beneath high-elevation seismogenic regions. In the Mackenzie Mountains, thicker crust is interpreted as due to crustal stacking from thrust sheet emplacement. The edge of this region of thickened crust is interpreted to delineate the extent of the former Laurentian margin beneath the NCC and is associated with a transition from thrust to strike-slip faulting observed in regional seismicity. More geographically extensive seismograph deployments at EarthScope Transportable Array density and scale will be required to further extend crustal-scale and lithosphere-scale imaging in western Canada.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".