Cane Stabilization Improves Yield of Red Raspberry (Rubus idaeus L.)
Bibliographic record
Abstract
Treatments of either staked (stabilized) or not staked (control, freestanding) canes were applied to Rubus idaeus L. `Boyne' and `Regency' during the 1997 and 1998 seasons to determine the effect of stabilizing fruiting canes in a windy environment. Treatments were applied in late April of each year, and canes were removed following harvest for growth analysis. Stabilizing (staking) floricanes increased yield per cane in `Boyne' by 68% and in `Regency' by 189%, primarily through increases in fruit number per cane. Leaf area of the staked canes was 41% larger for `Boyne' and 159% for `Regency' than that of the control canes, suggesting that more leaf area was retained for photosynthesis, resulting in greater yield. Primocane diameter in `Boyne' and primocane height in `Regency' were also increased by staking, but floricane structure was unaffected.
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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".