Phosphorus status on Canadian organic farms
Bibliographic record
Abstract
Abstract In eastern North America, many conventional livestock farms, especially dairy farms with high inputs of feed and fertiliser have excess soil phosphorus levels and an annual phosphorus surplus. However, a Canadian dairy farm in transition to organic, without fertiliser inputs reduced its farm P surplus to a marginal level. On long‐term organic dairy farms in Ontario, most soils tested low to very low in available P as measured by a standard soil test. Canadian Prairie organic grain farms also consistently demonstrate deficiencies in available soil P. Organic producers have few viable alternatives for P management. Phosphate rock can be acceptable to organic standards (provided they are low in heavy metals, and not processed synthetically), but the P in these becomes available slowly, especially in high pH soils common on most organic farms in Canada. An alternative is to increase soil P availability. Enhanced microbial activity in organically managed soils may make P more available. Livestock manures are rich sources of available phosphorus, but a majority of organic farmers in Canada do not keep livestock. Off‐farm manure sources are subject to organic regulations and hauling costs, both of which may be prohibitive. Furthermore, manure from conventional farms in Canada may be contaminated by genetically modified material from corn and soybean feed. Additional research is required to improve short‐term availability of soil P and long‐term replacement. Copyright © 2007 Society of Chemical Industry
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".