SORPTION OF HERBICIDES IN RELATION TO SOIL VARIABILITY AND LANDSCAPE POSITION
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using the soil-water sorption partitioning coefficient (Kd), this study quantified the spatial variation of 2,4-D sorption by soil in an undulating-to-hummocky terrain landscape near Minnedosa, MB, Canada. Herbicide sorption was most strongly related to soil organic matter content and slope position, with greatest sorption occurring in lower landscape positions with greater soil organic matter content. The relation between sorption and slope position was more pronounced under conventional tillage (CT) than under long-term zero-tillage (ZT). Using multivariate regression and three independent variables (soil organic matter content, soil clay content and soil pH), the prediction of herbicide sorption by soil was very good for CT (R2 = 0.89) and adequately for ZT (R2 = 0.53).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it