Effects of Re-Used Plastic Film Mulching on Soil Temperature and Sunflower’s Emergence
Bibliographic record
Abstract
Aiming at reducing agricultural pollution caused by plastic film, the study compared with new plastic film mulching and bare field, to investigating the effects of re-used plastic film mulching on soil temperatures, seed emergence and all seedlings period were studied in Hetao area, China. The results showed that, (1) compared with bare field, the soil temperature of re-used film mulching increased 1.3~4.0 °C and 0.7~1.8 °C separately in the highest and lowest temperature stage. The soil average temperature of upper soil layer (0~20 cm) increased 1.7~2.1°C, and 1.3~2.0 °C lower than new film mulching. (2) Compared with bare field, Daily maximum and minimum temperatures of re-used film mulching were postponed about 1 hour, similar as new film mulching. (3) During emergence stage (7 days after sowing), accumulated temperature of re-used film mulching was 21.6°Cand 23.8 °C higher than that of bare field in depth of 5 cm and 10 cm. Compared with new film mulching, it was 12.4 °Cand 10.0 °C lower in depth of 5 cm and 10 cm. (4) Mulching with re-used film could effectively shorten seed germination for 1-2 days and shorten all seedlings period for 2-3 days compared with bare field, and no difference with new film mulching.
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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 | 0.000 |
| 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".