A Study on the Soil Seed Bank Similarity between Different Dumping Yards and Their Nearby Forests in Jinanqiao Hydropower Station
Bibliographic record
Abstract
Dumping yards generated in Hydropower station construction are one of the most difficult places to restore,to know the relationship of soil seed bank between dumping yards and their nearby forests,a study on the soil seed bank similarity between different dumping yards and their nearby forests in Jinanqiao Hydropower Station was carried out based on seed germination trial.The results showed that the similarity coefficient between Meihe dumping yard platform and its nearby forest was highest of 0.46,the coefficient of 3# dumping yard platform(0.44) was lower than that,and the coefficient of 2# dumping yard platform was lowest of 0.27,it's show a rule that the coefficient descended with the distance and high difference between platform and its nearby forest became longer and larger,as far as the similarity coefficient between platforms and nearby forests are concerned.The similarity coefficient between platforms and nearby forests was larger than that between side-slopes and their nearby forests.Cruciferae and Compositae were dominant families in dumping yards,Cruciferae and Cyperaceae and Compositae were dominant families in their nearby forests,herb were dominant life form in both dumping yards and their nearby forests,17 species among 20 species in the dumping yards are the common species in the nearby forests,the similarity coefficient between the dumping yards and the nearby forests was 0.49.
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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 | 0.001 |
| 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 | 0.000 |
| 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".