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Record W4210510371 · doi:10.1201/9781003096856-16

Genetically Modified Cotton

2022· book-chapter· en· W4210510371 on OpenAlexaboutno aff
Iqrar Ahmad Rana, Allah Bakhsh, Shakhnozakhon Tillaboeva, Qandeel-e-Arsh, Muhammad Azhar

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsBt cottonBiologyBiotechnology

Abstract

fetched live from OpenAlex

Transgenic cotton is one of the earliest genetically modified crop plants grown globally. Field trials and biosafety evaluations on Bt cotton carrying Cry1Ac were started in 1993 and field plantations were permitted in 1996. This cotton resulted in a significant reduction in insecticide usage as lepidopteran insects were largely reduced in cotton fields though some of the minor pests (non-lepidopteran) could build their population in cotton fields. Though the resistance breakage against the said pests is reported intermittently, yet, through management strategies, Bt cotton is still grown worldwide in cotton-growing areas. Apart from this, new technologies (Bolgaurd, Bollgaurd-II, and Bollguard-III) are being developed continuously to increase the efficiency of Bt proteins and to control the resistance breakage by lepidopteran and certain other insect pests. This technology was introduced by Monsanto which is a big giant in the agriculture and seed sector and has been involved in farmers’ victimization in the US and Canada by suing them through courts of law for using their technology. Similarly, they commercialized their seed in India in collaboration with Mahyco, which reduced the cost of production for Indian farmers; yet, certain court and management issues, like the use of refuge seed, turned out to be irritants for Indian farmers. Pakistan could not yet benefit from Bollguard-II and Bollguarg-III, primarily due to the same policies. China, on the other hand, developed its own technologies alongside using technologies from Monsanto. Talking of the rest of the world, it will prove a boom if technologies are developed locally by the public sector, otherwise, the private sector may turn it into dust any time they don’t find their monitory benefits.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.958
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2100.001

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 head0.046
GPT teacher head0.230
Teacher spread0.184 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicGenetically Modified Organisms ResearchFrench-language works237,207