Evaluation of a modified sequential P extraction protocol: Quantification of Fe(<scp>II</scp>)‐P as a separate phase in seven different freshwater sediments
Bibliographic record
Abstract
Abstract Sequential phosphorus (P) extraction (SPE) is a well‐established and widely applied method for quantitatively and qualitatively determining the critical nutrient P in freshwater sediments. It allows the estimation of P bioavailability and facilitates the evaluation of the long‐term effects of eutrophication mitigation measures. Most current protocols do not differentiate between redox‐sensitive Fe(III)‐P and more stable reduced Fe(II)‐P minerals, such as vivianite. In this study, we tested a modified SPE protocol designed to quantify Fe(II)‐P (vivianite‐P) as a separate phase through the complexation of Fe(II) with 2,2′‐bipyridine (Bipy). Seven lakes were selected as study sites with different sedimentary Fe and P contents and restoration histories. We validated the Bipy extraction step through direct comparison with results from the conventional protocol and the application of direct mineral detection methods, including x‐ray absorption near‐edge structure at the Fe and P K‐edges, x‐ray diffraction, optical microscopy, and scanning electron microscopy with energy dispersive x‐ray spectroscopy. The Bipy fraction was primarily extracting P that was conventionally extracted in the bicarbonate‐dithionite (redox‐sensitive Fe/Mn‐bound) and NaOH (metal‐[Fe/Al‐]bound) fractions. The results from the direct detection methods indicated that the extracted Fe(II)‐P was predominantly vivianite. The efficiency of the Bipy extraction was decreased in samples with high crystallinity, but excessive Fe(II) or high organic content had minimal impact. Hence, it is highly recommended to use x‐ray diffraction and x‐ray absorption near edge structure in combination with the modified extraction protocol. Overall, the method tested with different freshwater sediments provides robust results when quantification of Fe(II)‐P including vivianite is an important objective.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".