Selection of trees species composition for creation of forest belts on newly created agrarian landscape of a regulated landfill
Bibliographic record
Abstract
Abstract Every year the number of landfills for municipal solid waste (MSW) is growing all over the world. Overloaded landfills are closed, followed by reclamation and creation of agricultural landscapes. Trees and shrubs must adapt to unfavorable environmental conditions in a reclaimed MSW landfill. As a result, plants resistance is reduced. We studied the safety of planted trees and shrubs, as well as their growth over three years of research, in order to study the adaptation of woody plants to the conditions of the reclaimed MSW landfill and the effect of soil on adaptation. Canadian maple, barberry and Siberian mountain as h were studied on the experimental site of the newly formed agricultural landscape at the reclaimed MSW test site. The MSW landfill is located in the northwestern part of the city of Barnaul. According to research, mountain ash has the lowest overall survival rate at about 2%, barberry at 33%, and Canadian maple has the highest overall survival rate at 81.25%. Canadian maple can be used on the newly created agricultural landscape of MSW landfill for forest reclamation purposes.
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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 | 0.001 | 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".