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Record W2790406477 · doi:10.6000/1927-5129.2018.14.07

Impact of Unequal Distribution of Canal Water on Farm Produce: A Case Study Matli Taluka

2018· article· en· W2790406477 on OpenAlexvenueno aff
Zareen Khan Rind, Ghulam Ali Jariko, Shahabuddin Mughal, Ghazala Umer Baghal

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsIrrigationRespondentWater scarcityEnvironmental scienceEconomic shortageWater resource managementAgricultureGeographyAgronomyGovernment (linguistics)

Abstract

fetched live from OpenAlex

This study seeks to investigate to identify the impact of shortage of water on the tail, end areas of the irrigation network. For the research study 320 respondents were randomly selected and nearly 107 from each category that is large medium and small farmer’s respondent. The sample further stratified respondents from all three reaches that is head middle and tail of main semi-irrigation channels and on the water courses level as well to capture the authentic picture of the water availability on each level of irrigation system. The observation of the study and data collected revealed that farmers on the head reaches benefit more from the supply of water from crop production compare to middle and tail reaches and middle reaches have more opportunity of having better irrigation water compare to the tail reaches however, the more sufferers are the tail reach farmers who get less water from crop production. Consequently, this situation cause’s absolute poverty to the farmers on the tail reaches of the irrigation water supply channels.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.038
GPT teacher head0.290
Teacher spread0.252 · 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 designBench or experimental
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

Citations0
Published2018
Admission routes1
Has abstractyes

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