The effect is soil quality on field scale run off under concentional and conservation tillage systems
Bibliographic record
Abstract
The National Soil Conservation Program (NSCP) is a research program managed and funded by Agriculture Canada. The program focuses on the improvement of agricultural soil and water quality through education and implementation of farm conservation practices. The program is multi-faceted in design and approach and includes several topics of study primarily in the soil quality and soil conservation areas. As part of the NSCP, Beak Consultants Limited (BEAK) conducted a study examining soil quality, agricultural runoff quality and groundwater quality, under conventional and conservation tillage systems. This research study focused upon field scale processes and encompasses two growing seasons. The study's primary objective was to examine the transport and fate of nutrients (primarily nitrate-N and phosphorus) and metolachlor, a commonly used pesticide in Southern Ontario, under two differing tillage management systems. This final report includes sections on literature review, study methods, study sites description and design, meteorology, soil quality assessment, surface water and groundwater monitoring and the effects of conservation and conventional tillage on soil and water quality within the study sites.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".