The inositol phosphates in soils and manures: Abundance, cycling, and measurement
Bibliographic record
Abstract
Giles, C. D., Cade-Menun, B. J. and Hill, J. E. 2011. The inositol phosphates in soils and manures: Abundance, cycling, and measurement. Can. J. Soil Sci. 91: 397–416. This review focuses on recent advances in understanding the origins, abiotic and biotic cycling, and measurement of inositol phosphates (IPx) in manures and soils. With up to eight orthophosphates bound to inositol via ester linkages, this class of compounds has the potential to be unavailable to enzymatic hydrolysis when sorbed or in complex with soil metals, limiting the release of phosphorus (P) for uptake by plants. However, hydrolysis of IPx by microbial phytases in aquatic environments could result in a potent source of the eutrophication agent orthophosphate. This review discusses the forms and stereoisomers of IPx that have been identified in environmental samples. Next, it discusses the various techniques used to identify IPx, including extraction and concentration, separation techniques such as electrophoresis, spectroscopic methods such as phosphorus-31 nuclear magnetic resonance spectroscopy (31P-NMR), mass spectrometry and X-ray absorption near-edge structure (XANES), and enzymatic techniques, such as enzyme hydrolysis (EH). Recent advances in knowledge about abiotic and biotic factors controlling the cycling of IPx in soil, manure and water are summarised, including soil characteristics affecting IPx sorption, transportation processes, and the microbial production and degradation of IPx. Finally, areas for future research focus are discussed.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".