Elucidating the nature of surface water - groundwater interactions beneath a large unregulated river system with the aid of AEM data
Bibliographic record
Abstract
SummaryThe Fitzroy River with its associated alluvial aquifer in northern Western Australia has been considered in planning for Perth’s future water supply and for agricultural development but its potential needs to be informed by detailed understanding of groundwatersurface water interactions occurring along its extent, and in particular must consider and account for the consequences that might arise when extracting groundwater from shallow and deep aquifers linked to this river system. Results from the interpretation of a regional scale longitudinal transect (~274 line kms) of SkyTEM helicopter EM data are presented which elucidate river-bed processes occurring along its extent. The AEM indicate a variable groundwater quality and related aquifer characteristics associated with different parts of the river. A 1D laterally constrained inversion (LCI), was examined against hydrochemical, environmental tracer (including 222Rn and Cl-), and hydrogeological data sampled longitudinally. Combined, they indicate a link between the Fitzroy’s alluvial aquifer system and with underlying Canning Basin sediments. The results demonstrate the value of regional, reconnaissance scale AEM surveys to better define groundwater processes beneath large unregulated river systems.
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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 | 0.000 |
| 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 | 0.000 | 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".