A multiple transmitter and receiver electromagnetic system for improved target detection
Bibliographic record
Abstract
In inductive electromagnetic (EM) geophysics, repeating measurement stations using multiple transmitter positions and summing these datasets into a single dataset can drastically improve the signal-to-noise (S/N) ratio from targets, especially deeper ones. The manner in which these datasets (one dataset per transmitter location) are summed depends on the target location and orientation. A simple method to estimate the target location and orientation is to compare the summed responses with a lookup table of known locations and orientations. Once the location and orientation is known, a new dataset can be created which will enhance the S/N ratio for that particular target. If multiple large moment transmitters are used (such as airborne transmitters) then S/N ratios significantly larger than large ground horizontal loops are possible. In a test ground time-domain EM survey, 25 transmitter positions were used and the location and orientation of a shallow target could be determined. The resultant summed profile had a larger S/N ratio and, as such, was easier to interpret.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".