Bibliographic record
Abstract
Cheng, B., Rakow, G., Olson, T., Williams, D. J. and Gugel, R. K. 2015. AAC Adagio yellow mustard. Can. J. Plant Sci. 95: 1043-1045. Mucilage content in yellow mustard (Sinapis alba L.) is an important seed quality parameter for the mustard trade since mucilage contributes to the consistency of prepared mustard products. Some wild type brown-seeded accessions of S. alba have much higher mucilage contents than have been observed in yellow-seeded cultivars and breeding lines. Increasing the mucilage content of cultivated, yellow-seeded S. alba by transferring the high mucilage trait from brown-seeded S. alba was initiated in 2004 at the Saskatoon Research Centre, Agriculture and Agri-Food Canada. The yellow mustard variety AAC Adagio with high mucilage content [96.8 centistokes (cst) g-1 seed] was successfully developed from crosses between the elite yellow-seeded breeding line SA00-PYM (mucilage: 35.2 cst g-1 seed) and five brown-seeded S. alba accessions (mucilage: 87.5-108.7 cst g-1 seed). AAC Adagio is well-adapted to all mustard growing areas of western Canada.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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".