Evaluating potential coal seam gas impacts to the Condamine Alluvium: an example of successful community involvement
Bibliographic record
Abstract
The groundwater resources of the Condamine River Alluvial Aquifer (Condamine Alluvium) in Queensland have been developed in the past 60 years for irrigation, stock, domestic and other uses. Extraction of more than 55,000 mL/yr from this aquifer is critical to supporting the local irrigation industry. Existing and proposed coal seam gas development in the Surat Basin extends to underneath the western edge of the CA footprint and involves depressurisation of coals that form up to 10% of the Walloon Coal Measures (WCM) at some depth below the alluvium. Reduced groundwater availability from the already-stressed Condamine Alluvium is thus an oft-quoted concern of landholders when further development of the CSG industry is considered. An extensive study, led by the Queensland Office of Groundwater Impact Assessment (OGIA) and supported by Arrow Energy, was carried out to provide quantitative assessments of vertical hydraulic conductivity between the alluvium, coal measures and intervening formations. This extended abstract focuses on one element of the aforementioned study led by Arrow Energy, specifically, aquifer testing undertaken at two representative sites overlying the Condamine Alluvium. This included drilling and collection of core; geophysical, geomechanical and geochemical testing; test pumping and monitoring; and, modelling. An important element of this project, aside from sharing of data and results—was the involvement of local landholders in development of the investigations, and attendance at field days during drilling and presentation of results. Key findings included estimated ranges of vertical hydraulic conductivity derived from parameter estimation modelling that were lower than previously suggested.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".