Correction: The effect of year and variety on the nutritional value of Camelina sativa meal
Bibliographic record
Abstract
Camelina [Camelina sativa (L.) Crantz] is emerging as a promising crop due to its high oil content of seeds with a predominance of unsaturated fatty acids, and good protein content of defatted meal. This study investigated the nutritional composition of defatted camelina meal obtained from four varieties (three from Canada and one from Austria) grown in the Padana Plain (northern Italy) for four consecutive years (2016–2019). Statistical analyses were performed based on the collected data. Principal Component Analysis (PCA) revealed distinct nutritional profiles among varieties and growing seasons. Calena, the Austrian variety, exhibited good nutritional quality and stability over the years. Pearl showed an intermediate year-to-year stability but promising values for trypsin inhibitors, condensed tannins and in vitro digestibility. The anomalous quantity of rainfall recorded during the early stage of seed development in 2019 allowed us to state that extreme climatic events can significantly affect the seed composition of the camelina varieties. This makes it clear that varietal and environmental factors need to be considered to produce a crop that can be fed to livestock.
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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 | 0.007 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.140 | 0.024 |
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".