Fitzroy River Basin, Queensland, Australia. IV. Identification of flood sediment sources in the Fitzroy River
Bibliographic record
Abstract
Environmental context. During flood events, the Fitzroy River is a major contributor to the loads of suspended sediment and nutrients to the southern Great Barrier Reef. The present geochemical and modelling study provides for the first time a quantitative estimate of the temporal variation in sediment sources over an entire flood hydrograph. Basaltic soils are substantially enriched in this flood event relative to their catchment abundance. Abstract. Suspended sediment collected over a complete flood hydrograph in the Fitzroy River provided an insight into the origin and transport of sediment in this system. Strong temporal trends are evident in the proportions of catchment soil types estimated using a Bayesian mixing model in the fine (<10 µm) fraction of the suspended sediment. These temporal trends were also manifested in changes in mineralogy, major and trace element and Nd–Sr and C–N isotope geochemistry. Tertiary Basaltic soils were the most abundant catchment soil type transported in the flood event studied here, constituting 39% of the <10-µm sediment fraction, but varied between an estimated 20 and 50% of the suspended solids over the course of the flood event. The techniques used here allow quantification and comparison between flow and suspended sediment sources and are widely applicable to other 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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".