Effective elastic thickness <i>T</i><sub><i>e</i></sub> of the lithosphere in western Canada
Bibliographic record
Abstract
A stochastic relationship between topography and Bouguer gravity is used to calculate high‐resolution variations in effective elastic thickness, Te, of the lithosphere in western Canada. The topography‐gravity coherence is calculated using a two‐dimensional, maximum‐entropy‐based spectral estimator. This method allows for smaller data windows and provides Te determinations with higher spatial resolution than standard Fourier spectral estimators. Our analysis shows significant variations in Te in western Canada. Te increases from ∼20–40 km in the weak, young portions of the Cordillera to 100 km and greater in the strong, old Canadian Shield. Te estimates are in good agreement with lithospheric temperatures calculated from surface heat flow and radioactive heat generation data. Our calculated Te distribution also shows strong correlation with other thermally related geophysical parameters, such as lithospheric age, regional heat flow, seismicity, seismic properties, and the stress field. Consequently, we infer that lithospheric temperatures exert a primary control on large‐scale variations in Te. Collectively, the correlations readily explain why the Craton continues to be stable and undeformed, whereas the Cordillera has continued to be deformed through the Cenozoic. An exception is the Wopmay Orogen, which includes the easternmost part of the northern Cordillera. There Te is ∼90 km, although the surface heat flow is ∼90 mW/m2. We infer that the high heat flow in this region is caused primarily by very high radioactive heat generation in the upper crust and that deep lithospheric temperatures are moderately low as expected from its age and long‐term geological stability.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".