Airborne gravity tests in the Italian area to improve the geoid model of Italy
Bibliographic record
Abstract
ABSTRACT Airborne gravimetry is an important method for measuring gravity over large unsurveyed areas. This technology has been widely applied in Canada, Antarctica and Greenland to map the gravity fields of these regions and in recent years, in the oil industry. In 2005, two tests in the Italian area were performed by ENI in cooperation with the Politecnico di Milano and the Danish National Space Center. To the knowledge of the authors, these were the first experiments of this kind in Italy and were performed over the Ionian coasts of Calabria and the Maiella Mountains. The Calabria test field is characterized by strong gravity variations due to the geophysical and topographic structure of the area. The ground gravity coverage is also quite dense. It was thus possible to compare airborne gravity with the ground observed values in order to check the precision of the airborne gravimetry. The second campaign was performed in an unsurveyed area centred on the Maiella Mountains, thus filling the data gap of this zone. Comparisons with existing ground data were also carried out in this area. After smoothing, the collected data have an accuracy of 2–3 mgal, as derived by cross‐over analysis. Moreover, the collocation method applied to compare and merge ground‐based and airborne data proved to be efficient and reliable. The standard deviation of the discrepancies between airborne data and collocation upward continued gravity is, in both cases, less than 8 mgal. In the Maiella test, the gravity field obtained by merging airborne and ground data using collocation also provides a more detailed description of the high‐frequency pattern of the geopotential field in this area.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".