Thermal thickness and evolution of Precambrian lithosphere: A global study
Bibliographic record
Abstract
The thermal thickness of Precambrian lithosphere is modeled and compared with estimates from seismic tomography and xenolith data. We use the steady state thermal conductivity equation with the same geothermal constraints for all of the Precambrian cratons (except Antarctica) to calculate the temperature distribution in the stable continental lithosphere. The modeling is based on the global compilation of heat flow data by Pollack et al. [1993] and more recent data. The depth distribution of heat‐producing elements is estimated using regional models for ∼300 blocks with sizes varying from 1°×1° to about 5°×5° in latitude and longitude and is constrained by laboratory, seismic and petrologic data and, where applicable, empirical heat flow/heat production relationships. Maps of the lateral temperature distribution at depths 50, 100, and 150 km are presented for all continents except Antarctica. The thermal thickness of the lithosphere is calculated assuming a conductive layer overlying the mantle with an adiabat of 1300°C. The Archean and early Proterozoic lithosphere is found to have two typical thicknesses, 200–220 km and 300–350 km. In general, thin (∼220 km) roots are found for Archean and early Proterozoic cratons in the Southern Hemisphere (South Africa, Western Australia, South America, and India) and thicker (>300 km) roots are found in the Northern Hemisphere (Baltic Shield, Siberian Platform, West Africa, and possibly the Canadian Shield). We find that the thickness of continental lithosphere generally decreases with age from >200 km beneath Archean cratons to intermediate values of 200±50 km in early Proterozoic lithosphere, to about 140±50 km in middle and late Proterozoic cratons. Using known crustal thickness, our calculated geotherms, and assuming that isostatic balance is achieved at the base of the lithosphere, we find that Archean and early Proterozoic mantle lithosphere is 1.5% less dense (chemically depleted) than the underlying asthenosphere, while middle and late Proterozoic subcrustal lithosphere should be depleted by ∼0.6–0.7%. Our results suggest three contrasting stages of lithosphere formation at the following ages: >2.5 Ga, 2.5–1.8 Ga, and <1.8 Ga. Ages of komatiites, greenstone belts, and giant dike swarms broadly define similar stages and apparently reflect secular changes in mantle temperature and, possibly, convection patterns.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".