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
To optimize cropping system benefits from pulse crops, it is important to understand their effects on subsequent crops. The objective of this study was to compare the effects of chickpea ( Cicer arietinum L.), lentil ( Lens culinaris Medik.), and pea ( Pisum sativum L.) stubbles on yield and quality of wheat ( Triticum aestivum L.), mustard ( Brassica juncea L.) or canola ( B. napus L.), and lentil or pea when grown on soils with clay and loam textures. This study was conducted between 1996 and 1999 in southwestern Saskatchewan. Rotational benefits of pulse crops (chickpea, lentil, and pea) to wheat appeared more consistent on the clay than the silt loam soil. Adjusting fertilizer N rates to account for estimated total N contribution from the previous pulse crop effectively neutralized the benefits on wheat yield and protein compared with the effects following mustard. Canola or mustard productivity was occasionally greater when grown on pea or lentil stubbles compared with mustard and wheat stubbles. The yield increase was attributed to increased available water. Under drier‐than‐normal conditions, pea yields were highest when grown on wheat stubble. Wheat productivity was least when grown on its own stubble. Pea and lentil provided rotational benefits to wheat, mustard, and canola and benefitted most from being grown in wheat stubble, indicating a strong fit for diversified cropping systems on the semiarid northern Great Plains.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it