Low resistivity anomalies in the upper crust of the Midlands of Tasmania from combined magnetotelluric datasets
Bibliographic record
Abstract
Heat flow data obtained in connection with geothermal resource exploration suggests anomalous upper crustal structure and processes in parts of central east Tasmania. The regional scale crustal geology of the Midlands of Tasmania is, however, mostly obscured at the surface by the Permo-Triassic sedimentary sequences of the Tasmania Basin together with extensive exposures of Jurassic dolerite. We investigate controls on undercover crustal processes in this region by combining long period and broadband magnetotelluric (MT) datasets in 3D inversions for the geoelectric structure; followed by an interpretation that is informed by aspects of the pre-existing 3D regional geological and geophysical model. The new 3D model allows improved resolution of low resistivity anomalies together with a qualitative appraisal of spatially variable model sensitivity. The most robust features (<1Ωm) in the 2–3 km depth interval occur where N–S and E–W faults intersect with a high point in the topography of the upper surface of a deep seated granite body. Enhancement of conductivity in this zone by clay, graphite or mineralisation, or a combination thereof, is likely. Other low resistivity features suggest that conductive pathways exist where major or multiple faults are present. These interpretations provide support for continued exploration in the Midlands of Tasmania for a variety of resources related to crustal fluids and fracturing.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".