intermontane belt, Northern Canadian Cordillera
Bibliographic record
Abstract
Using laboratory-derived temperature dependences of the electrical conductivity of mantle minerals coupled with appropriate mixing laws, we determine the bulk conductivity of mantle mineral assemblages for the ternary olivine– orthopyroxene–clinopyroxene (Ol–Opx–Cpx) system. We calculate physical property bounds (Hashin–Shtrikman bounds) as a function of the fraction of different phases present; these limits correspond to the extreme situations where the most conducting phase is either fully interconnected or fully disconnected. The relationships we present between temperature, mineral composition and bulk electrical conductivity allow constraining one of them given the other two. We apply this approach to an area of the North American Cordilleran Intermontane Belt in the Yukon Territory, northern Canada, where xenolith evidence indicates bimodal upper mantle mineral assemblages (harzburgite and lherzolite). This locality coincides spatially with an upper mantle region of low electrical conductivity determined by long period magnetotelluric data. Given the mantle mineral composition and the maximum and minimum bounds on the electrical conductivity, deduced by non-linear model appraisal, we determine the permitted extremal temperature bounds of the Intermontane belt mantle rocks directly below the Moho to a depth of some 80 km. We show that the mantle in this region is at a minimum temperature of 820 8C and a maximum temperature of 1020 8C; the latter is some 200 8C colder than that suggested in a recent interpretation of an observed collocated low velocity zone from a teleseismic survey. D 2005 Elsevier B.V. All rights reserved.Upper mantle temperature determined from combining mineral
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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 | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".