Enhancement of magnetic signatures of impact structures
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
Aeromagnetic surveys play an important role in the detection and analysis of terrestrial impact structures as large semi-regional aeromagnetic surveys are widely available.Impact craters can be divided into two groups based on morphostructure, namely simple and complex. Simple craters are relatively small bowl-shaped depressions with an upraised and fractured rim whereas complex craters are larger with a central uplift zone.Magnetic signatures of terrestrial impact craters vary greatly, reflecting the target rocks, the impact-related magnetisation and effects of crater fill and post-impact sediments. In basement rocks, the common signature is a magnetic low, ranging in amplitude from a few nT up to a few hundred nT. The central peak or ring uplift of crushed basement may produce strong magnetic highs. The magnetic signature may be due to shock demagnetisation, shock remagnetisation, and thermal and chemical remanent magnetisation effects. Impact craters in sedimentary targets are usually subdued and amplitudes of a few nT up to 10 nT are common.Enhancement of magnetic signatures of impact structures using filtering techniques is an important part of detection and analysis. Derivatives and shaded relief techniques, along with separation filtering, are probably the most used methods. Algorithms for fractional order derivatives and circular shaded relief have dramatically improved filter results. The fractional derivative order can be varied to optimise separation of the impact magnetic signature. Circular shaded relief treats all directions equally unlike the fade-out for features sub-parallel to the shading direction evident in conventional shading.The fractional order derivative and circular shaded relief algorithms are illustrated from impact structures in Australia and Canada in both basement and sedimentary cover rocks.
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 | 0.000 | 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) | 0.004 | 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