The effect of organic mulches and mycorrhizal substrate on growth, yield and quality of Gold Milenium apples on M.9 rootstock
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sas-Paszt, L., Pruski, K., Zurawicz, E., Sumorok, B., Derkowska, E. and Gluszek, S. 2014. The effect of organic mulches and mycorrhizal substrate on growth, yield and quality of Gold Milenium apples on M.9 rootstock. Can. J. Plant Sci. 94: 281-291. A 3-yr study was conducted to evaluate the effects of organic mulches and mycorrhizal substrate on growth and yield of apple cv. Gold Milenium grown on M.9 rootstock. Straw (rye), pine bark, conifer tree sawdust, compost (plant debris), cow manure, peat moss substrate (commercial), and mycorrhiza substrate (Mykoflor®, containing mycorrhizal fungi: Glomus intraradices, G. mosseae, G. etunicatum) were applied in spring of each year. All the applied treatments did not affect significantly the tree growth. Mulches did not have a positive effect on total soluble solids of the fruit and the number of fruits in different size categories. Only sawdust mulch significantly increased the number of fruit in size diameter class of 7.0-7.5 cm compared with the control. The use of mulches affected the concentration of macro- and microelements in leaves, particularly Cu, Fe, Mn and Zn. Mulches positively affected the pH and organic matter content of soil. The best results were observed with the use of the compost, cow manure and the mycorrhizal substrate, where the concentrations of P, K and Mg, most of microelements and soil organic matter were elevated.
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.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it