1, 2.5 and/or 3D Inversion of Airborne EM data - options in the search for sediment-hosted base metal mineralisation in the McArthur Basin, Northern Territory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The southern McArthur Basin in Australia’s Northern Territory is host to some Tier-1 sediment-hosted base metal mineral deposits including the McArthur River Zn-Pb-Ag mine. Airborne electromagnetic (AEM) data sets have been employed as a key exploration technology in the search for these mineral systems. A geological interpretation of results arising from the use of different inversion techniques, including a 1, 2.5 and 3D methods, was undertaken on a helicopter EM data set acquired over a structurally complex sediment package in the Batten Fault Zone north of the McArthur River Mine. The exploration targets were conductive, mineralised units (HYC pyritic shale member) associated with the Barney Creek Formation. Results from this study suggested that although the model fits were good, the derived conductivity models for the 2.5D and 3D inversions appeared to be smooth representations of geological reality, particularly when compared with data from drilling and surface geological mapping. Superficially, the 1D smooth model layered Earth inversions appear to map geological variability and structural complexity in greater detail even though the structures are more 3D in nature. IP effects are observed in the data and influence the modelled structure, but can be accounted for and complement the non IP 1D inversion results. The outcome of this study also indicates that when employing higher order inversion methods in the interpretation of AEM data sets, there may be significant benefit in asking a contractor/consultant for 1D inversion results as well. In the resulting interpretations if conductors appear in one but not the other, it is worth asking the question why?
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 0.000 |
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 it