Bibliographic record
Abstract
Abstract The basic reason for agricultural lands to be affected by waterlogging and salinity is the inadequacy of the natural drainage system to handle the water that reaches the land either by natural or artificial means. Under such situations, an artificial drainage system has to be provided. The meaning of land drainage varies in different regions and contexts. A geographer or a surface hydrologist may use it to mean the pattern of natural watercourses in a hilly area. A pedologist may think in terms of the permeability of a poorly drained or well‐drained soil. In Peru, engineers interpret drainage as reconstruction of natural waterways rather than removal of water. In Canada, it may mean reclamation of marshland for agricultural or urban development. In Holland, a Dutch farmer may use it for the installation of drainpipe in the soil. Thus, in different areas, this term implies different meanings and objectives. If the land use is primarily agricultural then land drainage could be defined as the establishment and operation of a system by which the flow of water from the soil is enhanced, so that agriculture can benefit from the subsequently reduced or controlled water level in the soil. Agricultural land drainage aims at reclaiming and conserving land for agriculture, to increase crop yields, to permit cultivating more than one crop in an area, and to reduce the cost of production.
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 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) | 0.029 | 0.003 |
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; both teacher heads agree on what is shown here.
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".