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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.004 | 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 teacher head, 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".