3D modelling and inversion of airborne gravity gradiometry and aeromagnetic data from Budgell Harbour, North-Central Newfoundland
Bibliographic record
Abstract
Airborne gravity surveys have been become a popular tool for mineral exploration in the past three decades, mostly because of considerable improvements in equipment. Airborne methods make the data acquisition process rapid, more straightforward, and potentially cheaper than ground surveys. 3D modeling and inversion of gravity gradiometry and aeromagnetic datasets from Budgell Harbour, located in north-central Newfoundland, are carried out. Reef-type platinum group mineralization is present in the area, as well as a large scale, deep igneous intrusion (the Budgell Harbour Stock). The intrusion is thought to be related to the same tectonic activity that resulted in the formation of the basins offshore Newfoundland that are now being actively explored for hydrocarbons. 3D modeling and inversion, specifically taking into account topography, are done for the gravity gradiometry and magnetic data-sets. The inversions are typical unconstrained, minimum-structure inversions. Joint inversion of the gravity gradiometry and magnetic data-sets is also considered. The Earth model is parameterized in terms of an unstructured tetrahedral mesh, which allows the topography to be modeled to the same accuracy with which it is known. The goal is to develop 3D density and susceptibility models of the area, thus further assessing the mineral potential of the area and better delineating the Budgell Harbour Stock.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".