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Record W2080485570 · doi:10.5539/jas.v3n2p178

Sustainable Development and Agriculture Sector: A Case Study of Sindh

2011· article· en· W2080485570 on OpenAlexvenueno aff
Muhammad Bachal Jamali, Nanik Ram, Ikhtiar Ali Ghumro, Faiz Muhammad Shaikh

Bibliographic record

VenueJournal of Agricultural Science · 2011
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureSustainabilityCroppingBusinessFodderAgricultural economicsSustainable developmentAgricultural scienceAgroforestryGeographyEconomicsEnvironmental scienceAgronomyEcology

Abstract

fetched live from OpenAlex

This research investigates the Sustainable Development and Agriculture Sector A Case Study of Sindh. Data were collected from 900 respondents from nine districts by using simple random technique, A Structural questionnaire was the basic tool for the measurement the sustainability in agriculture sector. It was revealed that diverting a sizeable area from the existing cropping sequence to other crops and enterprises to meet the ever-increasing demand for food, fibre, fodder, fuel while taking care of soil health and agro-ecosystem. The cost benefit analysis shows that they promise good returns to the farmers, though the returns on maize are not so promising. Natural conditions are particularly suitable to the districts of Nawabshah and Halla to the cultivation of maize. Similarly cotton may be a natural choice in Ghotki and Sukkur to reduce the cropped area under rice in the districts.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.157
GPT teacher head0.401
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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
Published2011
Admission routes1
Has abstractyes

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