Estimating overburden thickness in resistive areas from two-component airborne EM data
Bibliographic record
Abstract
An overburden with variable thickness can obscure the response of underlying geophysical features. For example, the gravity response of an increased thickness of low-density overburden might not be distinguishable from a deeper sandstone hydrothermally altered to clay. When the overburden is conductive, it’s thickness can be determined from the rate of decay of the off-time airborne electromagnetic data. However, the off-time decay of a thin or resistive overburden is small and difficult to measure. Previous studies have used the on-time resistive-limit response of a single component to successfully map apparent ground conductance in resistive areas. Quantitative resistive-limit models exist for thin-sheet, half-space, thin-sheet over half-space, and thick-sheet over half-space models. This study uses horizontal and vertical component data to estimate the thickness (and conductivities) of a two layered model across the survey profile. Presentation Date: Thursday, October 18, 2018 Start Time: 8:30:00 AM Location: 213B (Anaheim Convention Center) Presentation Type: Oral
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.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".