Analyse de l'étalement temporel de la floraison et influence sur la variabilité intra-arbre de la chute et de la croissance précoce des pêches
Bibliographic record
Abstract
This study attempted to explain peach abscission and early growth variabilities. We assumed that flower anthesis variability was indicative of early competition for carbohydrates, presumedly determinant for fruit set and early growth. From this viewpoint, the fruits resulting from early flowers should be advantaged. In a first step, we described and analysed the pattern of flowering dates within peach trees. In a second step, we studied the relationship between this pattern and the variability of fruit abscission and growth. At the tree level, the flowers started opening from the base towards the top, but at the shoot level the flowers opened from the apex down to the base. Single flowers opened 1 d earlier than associated flowers, which opened independently. However, the relationships between either fruit set or growth and date of flowering did not fit our hypothesis. For example, fruits from the late flowers had the best set. Thus, the initial hypothesis should be rejected while the influence of other factors should be considered. Our observations suggest that post-bloom temperatures could affect fruit set and early growth. Key words: Peach, Prunus persica, flowering, fruit abscission, fruit growth, early stage of development
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".