Impact of Different Water Management Scenarios on Corn Water Use Efficiency
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<abstract><title><italic>Abstract.</italic></title> <bold> </bold>This study investigated the water balance, crop yield, and water use efficiency (WUE) of a water table management system compared to a conventional drainage system at three nitrogen levels. A two-year field study was conducted using three blocks; each block was composed of two water management treatments: controlled drainage with subirrigation (CD-SI) and conventional or free drainage (FD). The water table depth was maintained at 60 cm below the soil surface in the CD-SI plots. Three nitrogen treatments (low, medium, and high) were applied in strips across all blocks. The seasonal water balance indicated surplus water conditions in the CD-SI plots, while the FD plots had deficit conditions. In 2008 and 2009, the corn grain WUE for the FD plots was 2.49 and 2.46 kg m<sup>-3</sup> respectively. The corn grain WUE for the CD-SI plots was 2.43 and 2.26 kg m<sup>-3</sup> in 2008 and 2009, respectively. The WUE of corn grain responded to the water treatments (p < 0.05) in 2009 but not in 2008. In 2009, at low and high nitrogen levels, the water management treatments demonstrated significant differences (p < 0.05) in grain yields. However, water management demonstrated no significant effect (p > 0.05) on grain yields at the normal nitrogen level. Furthermore, the two water treatments had no effect on the aboveground dry biomass yields in both years.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it