LitMod3D_4inv: Multi-observable and multi-scale geophysical inversions for the physical state of the Earth.
Bibliographic record
Abstract
<p>Characterising the physical state of the Earth's interior with high resolution requires the joint inversion of complementary geophysical datasets. LitMod3D_4inv is a method/software that allows regional and continental scale joint inversions within a probabilistic framework for the 3D thermochemical structure of the lithosphere and upper mantle. The software can simultaneously invert gravity anomalies, geoid height, gravity gradients, Love and Rayleigh surface-wave dispersion curves, receiver functions, body-wave travel times, surface heat flow, absolute elevation and magnetotelluric data, or any combination of them. The result is a collection of Earth models (a probabilistic distribution) with exceptional explicative power and robust estimates for uncertainties.</p><p>We use equations of state and Gibbs free energy minimisation routines to produce self-consistent sets of the seismic velocities, densities, and other properties from the actual parameters (unknowns) of the inversion – mantle chemical compositions, thermal profiles, and properties of the crustal layers (thickness, reference densities, Vp/Vs). The code relies on highly-optimised solvers for gravity, seismic, and magnetotelluric forward problems and multi-level hybrid parallel architecture to make use of multiple interacting markov chains. The modular structure of the code allows for extending the set of solvers to include new observables or to implement new Markov chain Monte Carlo algorithms.</p><p>In this presentation we will discuss recent developments in the LitMod3D_4inv suite and illustrate their performance with real examples in eastern Canada, in southern and central Africa, and north eastern Australia.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".