Insulative effect of plastic mulch systems and comparison between the effects of different plant types
Bibliographic record
Abstract
Abstract To address agricultural needs of the future, a better understanding of plastic mulch film effects on soil temperature and moisture is required. The effects of different plant type and mulch combinations were studied over a 3.5-month period to better grasp the consequence of mulch on root zone temperature (RZT) and moisture. Measurements of (RZT) and soil moisture for tomato (Solanum lycopersicum), pepper (Capsicum annuum) and carrot (Daucus carota) grown using polyolefin mulch films (black and white-on-black) were conducted in Ontario using a plot without mulch as a control. Black mulch films used in combination with pepper and carrot plants caused similar RZTs relative to uncovered soil, but black mulch film in combination with tomato plants caused a reduction in RZT relative to soil without mulch that increased as plants grew and provided more shade. White-on-black mulch film used in combination with tomatoes, peppers or carrots led to a reduction in RZT relative to soil without mulch that became greater than the temperature of soil without mulch. This insulative capability was similarly observed for black mulch films used with tomato plants. Apart from white-on-black film used in combination with tomatoes, all mulch film and plant combinations demonstrated an ability to stabilize soil moisture relative to soil without mulch. RZT and soil moisture were generally stabilized with mulch film, but some differences were seen among different plant types.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".