An Economic Efficiency Of Ground Water In Pudukottai District, Tamil Nadu
Bibliographic record
Abstract
Ground water has made significant contributions to the growth of India’s Economy and has been an important catalyst for its socio economic development. The State has as an area of 1.3 Lakh sq.km with a gross cropped area of around 63 L. Ha.. The Government's policy and objectives have been to ensure stability in agricultural production and to increase the agricultural production in a sustainable manner to meet the food requirement of growing population and also to meet the raw material needs of agro based industries, there by providing employment opportunities to the rural population. Tamil Nadu has all along been one of the states with a creditable performance in agricultural production with the farmersrelativelymoreresponsiveandreceptivetochangingtechnologies and market forces. Water used for irrigation should be essentially in good quality to grow good quantity crops, for the maintenance of soil productivity and for the protection of the environment. Physical and mechanical properties of soil, soil structure and permeability are very sensitive to the type of exchangeable ions present in irrigation water. Today, groundwater irrigation is becoming the cornerstone of providing water for agriculture, resulting in an overall exploitation rate of over 85%of the total available resources. Declining rates of tank and canal irrigation and overexploitation of groundwater are so critical that the state needs new policy interventions to tackle a pending water crisis. This policy brief recommends some development and investment options for the irrigated sector in Tamil Nadu.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".