AAC Sylvia-Arlene rose for rosehip production
Bibliographic record
Abstract
Fofana, B. and Sanderson, K. 2015. AAC Sylvia-Arlene rose for rosehip production. Can. J. Plant Sci. 95: 609-613. AAC Sylvia-Arlene is a semi-domesticated rose variety demonstrating quality and yield to meet the criteria for economic production. AAC Sylvia-Arlene was evaluated in Charlottetown between 2005 and 2012, and was found to be adapted in field and different agronomic practices. In comparison to the control lines S36, S68, S140, and S142, the line S26 was characterized as a natural interspecific hybrid of Rosa carolina×Rosa virginiana and was denominated as ‘AAC Sylvia-Arlene’ whereas S36 and S68 are Rosa virginiana species. AAC Sylvia-Arlene yielded more rosehips than all the control lines. The plants of AAC Sylvia-Arlene are taller and wider than those of the reference varieties. The flowers of AAC Sylvia-Arlene are light-pink, whereas those of S36, S140 and S142 are medium-pink. The fruits of AAC Sylvia-Arlene are longer and wider than those of the reference varieties. AAC Sylvia-Arlene's fruit contains more seed than that of S36 and S140, was similar to S142 and contains less seed compared with S68. The seed weight per fruit of AAC Sylvia-Arlene and S142 is lower than that of other references. The antioxidant capacity of AAC Sylvia-Arlene fruit was similar to that of S36 and higher than any other control lines. AAC Sylvia-Arlene showed a unique terpenoid content, higher than that of any other control lines.
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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) | 0.001 | 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) | 0.078 | 0.038 |
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".