The application of caesium‐137 measurements to investigate floodplain deposition in a large semi‐arid catchment in Queensland, Australia: a low‐fallout environment
Bibliographic record
Abstract
Abstract Floodplains comprise geomorphologically important sources and sinks for sediments and associated pollutants, yet the sedimentology of large dryland floodplains is not well understood. Processes occurring on such floodplains are often difficult to observe, and techniques used to investigate smaller perennial floodplains are often not practical in these environments. This study assesses the utility of 137Cs inventory and depth‐profile techniques for determining relative amounts of floodplain sedimentation in the Fitzroy River, northeastern Australia; a 143 000 km2 semi‐arid river system. Caesium‐137 inventories were calculated for floodplain and reference location bulk soil cores collected from four sites. Depth profiles of 137Cs concentration from each floodplain site and a reference location were recorded. The areal density of 137Cs at reference locations ranged from 13 to 978 Bq m–2 (0–1367 Bq m–2 at the 95% confidence interval), and the mean value ± 2 (standard error of the mean) was 436 ± 264 Bq m–2, similar to published data from other Southern Hemisphere locations. Floodplain inventories ranged from 68 to 1142 Bq m–2 (0–1692 Bq m–2 at the 95% confidence interval), essentially falling within the range of reference inventory values, thus preventing calculation of erosion or deposition. Depth‐profiles of 137Cs concentration indicate erosion at one site and over 66 cm of deposition at another since 1954. Analysis of 239+240Pu concentrations in a depositional core substantiated the interpretation made from 137Cs data, and depict a more tightly constrained peak in concentration. Average annual deposition rates range from 0 to 15 mm. The similarity between floodplain and reference bulk inventories does not necessarily indicate a lack of erosion or deposition, due to low 137Cs fallout in the region and associated high measurement uncertainties, and a likely influence of gully and bank eroded sediments with no or limited adsorbed 137Cs. In this low‐fallout environment, detailed depth‐profile data are necessary for investigating sedimentation using 137Cs. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 | 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) | 0.000 | 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".