3D inversion of DC/IP data using adaptive OcTree meshes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Data acquired from a direct current (DC) and induced polarization (IP) survey can be used to recover the conductivity and chargeability structures of the subsurface of the earth. In order to maximize the value of such a survey, the data should be inverted in 3D. As surveys get larger and targets get more complex, the discretization applied in regular rectilinear meshes can become cumbersome, resulting in prohibitively large numbers of cells. This problem is exacerbated in the presence of severe topography, or in cases of irregular survey geometry. Applying an adaptive OcTree mesh structure, it is possible to obtain fine resolution cells in regions of high variability without adding unnecessarily small cells where they are not required. This results in a vastly decreased number of cells, without penalizing the potential for high resolution recovered models. We develop the DC/IP inverse algorithm on the Oc-Tree mesh, and apply it to a field example from South America.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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