Terraced Pasture Changes the Soil Moisture Dynamics
Bibliographic record
Abstract
Climate changes, loss of biodiversity, soil degradation, scarcity and pollution of waters are the problems caused and experienced by society. The conservation methods of soil moisture are important for plant growth and groundwater preservation. The aim at this study was to evaluate the impacts of the terraces on soil moisture and to analyze the efficiency of Ground Penetration Radar (GPR) in the soil moisture determination. Soil moisture was determined by gravimetric and GPR methods in the depths of 0 to 10, 10 to 30, 30 to 60 and, 60 to 100 cm. The water storage in depth was larger and uniform in terraced than in the non-terraced pasture. However, the non terraced pasture has less soil compaction. Thus, the terrace does not guarantee adequate pasture management and other alternatives for sustainable management of cattle and reduction of soil compaction is necessary. The GPR method may be used to estimate the soil water content in volumetric basis in the field of a non-invasive manner. However, there need to study and determine the accuracy in GPR measurement in different methods and soil types.
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.
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) | 0.002 | 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".