Toward a transdisciplinary and unifying definition of legacy phosphorus
Bibliographic record
Abstract
Legacy phosphorus (P) is a concept advanced by Dr. Andrew Sharpley and colleagues that was originally applied to the persistence of anthropogenic signatures in watersheds, and it has since been adopted in a diversity of settings to help guide the science and management of P. Following Sharpley's example to develop consensus-based science, we considered contrasting perspectives on legacy P and defined legacy P as those stores within the environment that arise from historic human activity excluding "natural" or "background" geogenic sources. Legacy P is not restricted to one system or setting; it may reside in soils, sediments, biota, and water bodies. Legacy P has been estimated by fluxes (inputs minus outputs of P to a system) or, equivalently, by mass stocks (total minus geogenic). Because the origin of P in the environment cannot currently be directly quantified, we recommend that researchers report "total P" to track wider watershed P stocks and fluxes of P that include legacy P. We recognize that the definition of legacy P will continue to evolve as we continue to work toward consensus. Ultimately, the final definition of legacy P has consequences for the implementation and success of regulatory and voluntary strategies for legacy P management in agricultural systems. We support continued progress toward a consensus-backed, research-grounded definition for legacy P that is widely applicable yet useful for guiding management and policy.
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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 | 0.085 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.008 | 0.055 |
| Scholarly communication | 0.021 | 0.042 |
| Open science | 0.007 | 0.019 |
| Research integrity | 0.009 | 0.026 |
| Insufficient payload (model declined to judge) | 0.002 | 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".