Camelina seed quality in response to applied nitrogen, genotype and environment
Bibliographic record
Abstract
Jiang, Y., Caldwell, C. D. and Falk, K. C. 2014. Camelina seed quality in response to applied nitrogen, genotype and environment. Can. J. Plant Sci. 94: 971–980. Camelina (Camelina sativa L.), Brassicaceae, has great potential for food and industrial use. This study analyzed the seed oil content, oil yield, protein content, protein yield, as well as fatty acid profile relative to varying nitrogen (N) rates and in different genotypes under several environmental conditions. Seed samples were obtained from a 2-yr field study with five environments (site-years), five genotypes, and six N rates. Applied N increased protein content, protein yield, oil yield, and polyunsaturated fatty acids (PUFA), but decreased oil content and monounsaturated fatty acids (MUFA). Saturated fatty acids did not respond consistently to applied N. Lower air temperatures during the reproductive stages increased the total seed oil content, but the fatty acid composition was not affected. The experimental line CDI007 had the highest oil content, oil yield, protein yield, and PUFA, but contained the lowest protein content and MUFA. CDI002 contained the highest protein content and PUFA. CDI005 had the highest amount of MUFA. CDI008 was not considered to be a promising genotype since it had the lowest oil content and highest amount of saturated fatty acids.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".