AAC Network hard red winter wheat
Bibliographic record
Abstract
AAC Network is a semi-dwarf hard red winter wheat (Triticum aestivum L.) cultivar that is well adapted across western Canada and eligible for grades of Canada Western Red Winter (CWRW) wheat. It was developed using wheat × maize pollen doubled haploid methodology. AAC Network was evaluated in the Western Canadian Winter Wheat Cooperative registration trials relative to CDC Buteo, Emerson, Moats, and AAC Elevate for 4 yr (2016–2019). Based on 44 replicated trials, AAC Network produced grain yield similar to AAC Elevate, the highest yielding check, with a protein concentration 0.9 units higher. AAC Network had fair to good winter survival, relatively late maturity, short straw with excellent lodging resistance, and high test weight. AAC Network expressed resistance to stem and stripe rust, moderate resistance to leaf rust and common bunt, and intermediate resistance to Fusarium head blight. In addition to increased grain protein concentration, AAC Network showed improvements in gluten strength and flour water absorption, and it maintained the excellent milling yield and low flour ash attributes of the CWRW wheat class.
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".