Equilibration depth and temperature of Neogene alkaline lavas in the Cordillera of Alaska and Canada as a constraint on the lithosphere–asthenosphere boundary
Bibliographic record
Abstract
We have estimated the geochemical equilibration depth and temperature of the widespread Neogene alkaline basalts in the Cordillera of Alaska, Northwest Canada, and in Mexico using geobarometry on bulk compositions that have been minimally differentiated in upward transit. The method has uncertainties of about ±10 km and <70 °C. The regional averages of geochemical equilibration depth for 12 sites in Alaska vary from 50 ± 10 to 84 ± 2 km, somewhat broader than those from the Cordillera in western Canada, western USA, and Mexico. There are no associations of depth with terranes or geological provinces. The final equilibration depth of lavas with the surrounding mantle is concluded to be where partial melt percolating from greater depths’ ponds at the lithosphere–asthenosphere boundary (LAB) until it becomes gravitationally unstable and moves upward in conduits. The top of the low velocity zone from seismic receiver functions, taken to be the LAB in regions of Alaska where Neogene volcanism occurs, varies from 60 to 85 km, covering the range of geochemical equilibration depths of the alkaline lavas. A mean lava equilibration depth of 65 ± 10 km occurs in 24 of 36 alkaline volcanic centers from Alaska to Mexico, and several other global locations, suggesting the LAB may be controlled to a first order by the change in H2O storage capacity and viscosity across the garnet–spinel peridotite phase change at this depth. The scatter and variation in equilibration depths and temperatures are a factor of 2 greater than the recognized uncertainties, and are not yet explained.
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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 | 0.001 | 0.001 |
| 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".