Processing of Airborne Gamma-Ray Spectrometry using Inversions
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
Standard processing of Airborne Gamma-Ray Spectrometry data generally gives good results when the geological situation is uniform and the conditions of measurements are quite constant within footprint area with possible exception of flight height variations in a small range. Any violation of these conditions leads to certain problems. In reality, violations such as large changes of flight height and/or rugged terrain are not that rare as well as sharp changes in composition of surface rocks. This article proposes an approach where the solutions of inverse problems are used for data processing. The approach is quite natural in the processing of field data measured along the flight lines: it explicitly takes into account one-dimensional models of survey and flight parameters -from topography to sources distribution on the surface. Also, it clearly demonstrates that the inverse problem of Airborne Gamma-Ray Spectrometry data does not have a unique solution. This feature can be used in accordance with the geological problem in hands because various formulations of inverse problems can lead to various geological solutions. The use of the approach is illustrated by several examples given for both flight lines and survey areas.
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 | 0.001 |
| 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