Mixtures of paper mill sludge, wood chips, bark, and peat in substrates for pot-in-pot shade tree production
Bibliographic record
Abstract
There is little scientific information on substrates for pot-in-pot shade tree production. The objective of this research was to examine various organic-waste-derived substrates for growing shade trees in pot-in-pot systems. Seedling whips of green ash (Fraxinus pennsylvanica Marsh.), Japanese birch [Betula platyphylla var. japonica (Miq.) Hara], and silver maple (Acer saccharinum L.) were grown for two seasons in 76-L containers. The containers were trickle irrigated and fertilized with controlled-release fertilizers. Treatments included a control nursery mix (50% by volume of pine bark:15% compost:35% topsoil) and nine other mixes classified into three groups: Group I (25, 50 or 75% bark mixed with 50, 25, or 0% wood chips, and 25% paper mill sludge); Group II (25, 50 or 75% bark; 50, 25 or 0% wood chips; and 25% peat); and Group III (25, 50 or 75% peat; 50, 25 or 0% wood chips; and 25% paper mill sludge). In both years, trunk diameters of the three species were greatest with Group III substrates, intermediate with Group II, and least with Group I. Trunk growth was positively correlated with water retention porosity, which ranged from 42 to 57%, 38 to 42%, and 20 to 27% for Groups III, II, and I, respectively. Trunk diameters of Group II and III trees were equal to, or slightly exceeded (10–12%), those of the nursery mix. The nursery mix had a water retention porosity of 49% and generally the highest content of soluble salts. The high-peat (50 and 75%) substrates marginally but consistently produced trees with the largest trunk diameters, although with birch (not the other species) shorter trees resulted as the peat content increased. Key words: In-ground containers, nursery, ornamentals, waste utilization, container culture
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".