Performance of ‘Modi®’ Apple Trees on Several GenevaRootstocks Managed Organically: Five-Year Results From the 2015NC-140 Organic Apple Rootstock Trial
Bibliographic record
Abstract
In 2015, an orchard trial of ten apple rootstocks was established at ten locations in the United States and Canada using ‘Modi®’ as the scion cultivar. Trees were managed in accordance with United States organic standards to expose these rootstocks to the nutrient conditions and biome typically associated with organic tree-fruit production. Rootstocks included nine named Cornell-Geneva clones [Geneva® 11 (G.11), Geneva® 30 (G.30), Geneva ® 41 (G.41), Geneva® 202 (G.202), Geneva® 214 (G.214), Geneva® 222 (G.222), Geneva® 890 (G.890), Geneva® 935 (G.935), and Geneva® 969 (G.969)] and M.9 NAKBT337. All trees were spaced 1 x 3.5 m and trained using the tall spindle system. After 5 years, the greatest mortality was for trees on M.9 NAKBT337 (14%). Rootstocks separated into size classes from large semi-dwarf to small dwarf. G.890 resulted in large semi-dwarf trees, and G.202 produced moderate semi-dwarfs. G.41 and G.30 resulted in small semi-dwarf trees, and trees on G.935 were large dwarfs. G.11, G.214, G.969 and M.9 NAKBT337 resulted in trees that were moderate dwarfs, and G.222 resulted in small dwarf trees. The most yield efficient (cumulatively, 2016-19) trees in the trial were on G.935, G.11, and G.969, and the least efficient trees were on G.202 and G.890. The largest fruit (2016-19) were harvested from trees on G.30, G.41, G.890, and M.9 NAKBT33, and the smallest were harvested from trees on G.202.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".