Physicochemical Indices of Ground Water and Their Geoponic Management, in Coastal Odisha, India
Bibliographic record
Abstract
Agriculture can not exist without water. At present the old practice of arbitrary use of water in irrigation sector has become unethical. Odisha is an agrarian state in east coast of India. For better yield of crops, quality of water is intricately related to the aquifer geometry, ground water flow regime and its quality. Coastal Odisha is having an area of 14700 sqkm and demography of 1.26 million. The land has mostly water logged alluvial crop land, deciduous forests or sandy dunes with an astomosed channels of hexa-deltaic rivers. The edaphic factors demand improvement of quality of ground water which is brackish. The physicochemical properties like pH value, electrical conductivity, inorganic constituents (Na+, Mg++, Ca++, K+) of ground water used for lift irrigation have been studied. Data from thousand number of wells from the study area are covered in various seasons during the years 2009-2014 along with the yield of the major crop, i.e., paddy. The indices and parameters like EC, SAR, KI, ESP, SSP, MAR, PI and alkalinity of the ground water are determined to show its fitness for irrigation in the area. The different water management policies and present activities are discussed so that the ground water can be used efficiently for irrigation in coastal Odisha.
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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 | 0.003 |
| 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) | 0.001 | 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 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".