Context for re-evaluating agricultural source phosphorus loadings to the Great Lakes
Bibliographic record
Abstract
Joosse, P. J. and Baker, D. B. 2011. Context for re-evaluating agricultural source phosphorus loadings to the Great Lakes. Can. J. Soil Sci. 91: 317–327. Over the past decade, scientists have been discussing the re-emergence of harmful algal blooms and excessive growth of Cladophora in some areas of the Great Lakes. An observation that has emerged from these discussions is that management of non-point or diffuse sources of phosphorus will be more important in the future in order to address symptoms of eutrophication in the nearshore. This paper provides context for this renewed focus on managing non-point source tributary loads and is based primarily on materials and discussions from the Great Lakes P Forum. There are changes that have occurred in the lakes and tributaries in the past 15 yr that indicate a greater need to focus on non-point sources, whether urban or rural. Changes have also occurred in land management to reduce non-point P losses from agriculture. While these changes have reduced sediment and particulate P loading in some Ohio tributaries, the more bioavailable, dissolved P forms have increased. As there is incomplete knowledge about the mechanisms that are influencing algal growth, it could be a challenge to demonstrate, in the near term, improvements in water quality with further P reductions from agriculture alone. Regardless, there appears to be a desire for improved accountability and transparency for agricultural non-point source P management.
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 | 0.050 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.009 | 0.015 |
| 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".