Allelopathic effect of Siberian iris (Iris sibirica) on the early growth of wild oat (Avena fatua) and Canada thistle (Cirsium arvense)
Bibliographic record
Abstract
During 2015 a laboratory and greenhouse experiments were carried out to explore the allelopathic potential of different plant parts of Siberian iris on wild oat and Canada thistle early growth. The aqueous filtrates of Siberian iris rhizomes produced a strong inhibitory effect on germination, radicle and hypocotyl length and seedling weight of wild oat. Contrary, germination, radicle and hypocotyl length of wild oat was not significantly reduced by any Siberian iris leaves filtrate concentrations, but seedling weight of wild oat was significantly reduced at the 1/1 and 3/4 filtrate concentrations of Siberian iris leaves, relative to control. Similar, germination, hypocotyl length and seedling weight of Canada thistle, were significantly affected by the aqueous filtrates of Siberian iris rhizomes, and while same parameters were none significantly reduced by the aqueous leaves filtrates of Siberian iris in compare with the control. In green house experiment, all treatment with different Siberian iris rhizomes residues significantly affected density, height and fresh weight of wild oat plants. Opposite, no one treatment by Siberian iris leaves residues caused significant reduction of plants density, height and fresh weight of the wild oat plants in compare with the control. All Siberian iris mixtures with rhizomes residues highly significant decreased Canada thistle plants density in average for 60.1%, and fresh weight for 60.3% in compare with the control. No one treatment by Siberian iris leaves residues caused significant reduction of plants density and height of Canada thistle, but 1/1 and 1/2 residues mixtures of Siberian iris leaves significantly reduced its fresh weight.
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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 | 0.000 | 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 | 0.001 |
| 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 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".