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Record W2905494863 · doi:10.22617/wps189710-2

Investment in Research and Development for Basmati Rice in Pakistan

2018· paratext· en· W2905494863 on OpenAlexfundno aff

Bibliographic record

VenueADB Central and West Asia working paper series · 2018
Typeparatext
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Practices
Canadian institutionsnot available
FundersMalaysian Palm Oil BoardPakistan Agricultural Research CouncilInternational Fine Particle Research InstituteAlberta Agricultural Research Institute
KeywordsInvestment (military)Research developmentBusinessAgricultural economicsBiotechnologyEconomicsBiologyPolitical scienceBotany

Abstract

fetched live from OpenAlex

10 Impulse Response Functions for the VAR-X Model for the Value of Basmati Rice Exports from Pakistan BOX Excerpts from the Economic Survey of Pakistan v ABstRACtBasmati rice is Pakistan's celebrated export.After years of growth, Pakistan's production and export of basmati has slipped and is on a downward trend.The absence of a strong research and development institutional structure makes it extremely difficult for the sector to prepare for new challenges.The status of basmati rice as a major export commodity hides the fact that its contribution is below its potential.Without a policy commitment to elevate basmati rice as a strategic product, it will continue to be impacted by changing economic and environmental conditions.Extra funding for basmati can be easily channeled from the levy that is being collected from its export or through government development funds.The bigger challenge is changing the embedded mindset that fails to connect research and development with the production and commercialization of basmati.

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)0.000
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 score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.002

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 head0.087
GPT teacher head0.317
Teacher spread0.230 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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