Evaluation of morphological traits of flowers and crossing possibility of haskap ( <i>Lonicera</i> L.) cultivars depending on their origin
Bibliographic record
Abstract
BACKGROUND: Haskap ( Lonicera L.) is as a new perspective berry species for growing in temperate region climate. According to nowadays knowledge haskap is absolutely self-sterile species hence the studies on pollination mode are required. OBJECTIVE: The aim was to evaluate new haskap cultivars of Canadian and Russian origin in terms of their matching for cross-pollination. METHODS: The overlapping of flowering time of cultivars for mutual cross pollination was selected. The effectiveness of pollination was assessed: in terms of pollen tube overgrowth through the pistil tissue and the quality of set fruit. RESULTS: The Russian cultivars bloomed much earlier than the Canadian cultivars. The stigma is most receptive in the freshly open flower stage and directly after the anther burst. The minimum qualitatively acceptable weight of a berry is 1 g, which corresponds to the formation of about 6 seeds in the fruit. The most compatible pairs of cultivars were: ‘Aurora’בJugana’, ‘Aurora’בSinij Utes’ and ‘Aurora’בVostorg’. CONCLUSION: The Russian cultivars bloomed much earlier than the Canadian cultivars, the stigma is most receptive in the freshly open flower, minimum qualitatively acceptable weight of berry is 1 g (what represents 6 seeds in fruit), best mutual pollinating cultivars are the cultivars within the same breeding group (Russian x Russian and Canadian x Canadian)
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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 | 0.001 | 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".