Stochastic inversion of a gravity field on multiple scale parameters using surface and borehole data
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT A 3D stochastic inversion method based on a geostatistical approach is presented for three‐dimensional inversion of gravity on multiple scale parameters using borehole density and gravity and surface gravity. The algorithm has the capability of inverting data on multiple supports. The method involves four main steps: i) upscaling of borehole densities to block densities, ii) selection of block densities to use as constraints, iii) inversion of gravity data with selected block densities as constraints and iv) downscaling of inverted densities to small prisms. Two modes of application are presented: estimation and simulation. The method is first applied to a synthetic stochastic model. The results show the ability of the method to invert surface and borehole data simultaneously on multiple scale parameters. The results show the usefulness of borehole data to improve depth resolution. Finally, a case study using gravity measurements at the Perseverance mine (Quebec, Canada) is presented. The recovered 3D density model identifies well three known deposits and it provides beneficial information to analyse the geology of massive sulfide for the domain under study.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it