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Record W3143531964 · doi:10.6000/1927-5129.2013.09.58

Ex Post Impacts of Chashma Right Bank Irrigation Project on Cropping Pattern in D.I. Khan district, Pakistanc

2013· article· en· W3143531964 on OpenAlexvenueno aff
Atta‐ur Rahman, Amir Nawaz Khan

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsCroppingWater resource managementIrrigationGeographyHydrology (agriculture)ForestryEnvironmental scienceAgricultureGeologyArchaeologyEcologyGeotechnical engineeringBiology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.242
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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