Validating the Gedex HD-AGG™ Airborne Gravity Gradiometer
Bibliographic record
Abstract
The Gedex High-Definition Airborne Gravity Gradiometer (HD-AGG™) was designed and developed to deliver measurements of the gravitational field with improved signal-to-noise and resolution. The system has been under development for more than 10 years and has reached the point of commercial deployment. Knowledge of the gradiometer components being measured, noise character and resolution of the system will allow end-users to select exploration targets and determine survey parameters appropriately.The validation of the Gedex system has been progressive in nature consisting of laboratory tests and flight tests in a Cessna Caravan. The lab experiments consisted of static tests to establish the quiescent noise floor, signal confirmation tests and dynamic testing on a 6 degree-of-freedom shaker. The airborne testing included high altitude flights to confirm the noise level and character of the system over long periods. Low-level repeat surveys were carried out to establish the noise levels under survey conditions. High resolution terrain data were used to confirm the resolution of the system. Datasets from our validation program and the path forward are discussed.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".