Tillage systems and nutrient sources affecting soil cover, temperature and moisture in a clayey oxisol under corn
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
Tillage affects soil physical properties, e.g., porosity, and leads to different amounts of mulch on the soil surface. Consequently, tillage is related to the soil temperature and moisture regime. Soil cover, temperature and moisture were measured under corn (Zea mays) in the tenth year of five tillage systems (NT = no-tillage; CP = chisel plow and single secondary disking; CT = primary and double secondary disking; CTb = CT with crop residues burned; and CTr = CT with crop residues removed). The tillage systems were combined with five nutrient sources (C = control; MF = mineral fertilizer; PL = poultry litter; CS = cattle slurry; and SS = swine slurry). Soil cover after sowing was greatest in NT (88 %), medium in CP (38 %) and lowest in CT treatments (< 10 %), but differences decreased after corn emergence. Soil temperature was related with soil cover, and significant differences among tillage were observed at the beginning of the growing season and at corn maturity. Differences in soil temperature and moisture in the surface layer of the tilled treatments were greater during the corn cycle than in untilled treatments, due to differences in intensity of soil mobilization and mulch remaining after soil management. Nutrient sources affected soil temperature and moisture in the most intense part of the corn growth period, and were related to the variation of the corn leaf area index among treatments
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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