Negative and positive aspects of the presence of Canadian goldenrod in the environment
Bibliographic record
Abstract
Abstract Canadian goldenrod ( Solidago canadensis L.) is classified as an invasive plant species in many Eurasian countries. The species shows a great ability to environmentally spread in a variety of habitats, anthropogenic ones included. Based on the literature data, the paper discusses the negative effects of the presence of S. canadensis in the environment, including the reduction of biodiversity in plants and some species of insects and insectivorous birds. The occurrence of goldenrod clusters also contributes to soil degradation. Positive aspects related to the presence of S. canadensis are also discussed in the paper. Goldenrod can be used in the phytoremediation of soils contaminated with heavy metals and as an energy plant. Its extracts are effective in controlling the bloom of some algae in water reservoirs and in fighting fungal and bacterial diseases in plants. Goldenrod inflorescences’ abounding nectar allows for the efficient harvesting of honey. Both the inflorescences and the leaves of the plant are a valuable herbal raw material with a wide spectrum of activity, including its impact on gram-positive and gram-negative bacteria and yeasts. For these reasons, goldenrod deserves special attention in environmental research.
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 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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".