Multi-physics, inter-disciplinary approaches for groundwater system investigations and hydrogeological assessments in Northern Australia
Bibliographic record
Abstract
SummaryThe development of Northern Australia has been identified as a national priority, with water availability being fundamental to economic development. Surface water options are limited hence identification of new groundwater resources and water banking options is essential. Over the past four years, Geoscience Australia, in concert with State and Territory partners, has been involved in focussed groundwater investigations in 10 geographic areas as well as broader regional investigations (Figure 1). New data acquisition has included airborne electromagnetics (AEM); drilling (sonic, rotary mud, air core and diamond); slug and bore testing; ground geophysics (surface nuclear magnetic resonance, microgravity, passive seismic, seismic reflection and ground penetrating radar); borehole geophysics (induction, spectral gamma, nuclear magnetic resonance); hydrochemical and hydrodynamic analysis; age dating of water and landscape materials; and mapping (geomorphic, morphotectonic, regolith, geological and hydrological). These investigations inform hydrogeological assessments and water allocation planning.Overall, this multi-physics, inter-disciplinary approach has been critical in enabling the rapid identification and assessment of significant new potential fresh groundwater resources within tectonically inverted Palaeozoic sedimentary basins in the Fitzroy Basin (WA), Bonaparte Basin (WA-NT), Wiso Basin (NT), and Southern Georgina Basin (NT), and helped define the extents of a new groundwater resource for the town of Alice Springs (NT). Potential brackish and saline groundwater resources have also been identified in Cenozoic paleovalleys and Tertiary and Paleozoic Basins.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".