Ex Post Impacts of Chashma Right Bank Irrigation Project on Cropping Pattern in D.I. Khan district, Pakistanc
Bibliographic record
Abstract
This paper carries out the ex post environmental impacts of Chashma Right Bank Irrigation Project (CRBIP) on the cropping pattern of district D.I. Khan, Pakistan. Work on the Chashma Right Bank Canal (CRBC) was started in 1984 and subsequently completed in three stages during 2003-2004. The total cultivable command area of CRBC is 250,000 ha. It commands only left bank area as the slope is from west to east. It spreads over the two provinces i.e. Khyber Pakhtunkhwa and Punjab. The ultimate goal of the CRBIP was to enhance agricultural productivity, employment opportunities and alleviate poverty. The analysis revealed that there had been large scale changes in the agricultural system, with the construction of CRBC in the arid tract of district D.I. Khan. These changes were both positive and negative. After the advent of CRBC, acreage of both Kharif (summer) and Rabi (winter) crops has improved. The analysis revealed that positive changes have occurred in rice, sugarcane, pulses, wheat, barley, orchards and vegetables. Contrary to this, negative changes were registered in sorghum, millet, oilseed, barley and maize. While comparing the ex post changes in the cropping system, new water loving crops has been introduced as a result of CRBC. It has directly affected the water-table. It was found from the analysis that water-table is inclining at a rapid pace and is serious threat to the crop area.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".