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Record W2753793825 · doi:10.6000/1927-5129.2017.13.75

Effect of Different Synthetic Pesticides Against Pink Bollworm Pectinophora gossypiella (Saund.) On Bt. and non-Bt. Cotton Crop

2017· article· en· W2753793825 on OpenAlexvenueno aff
Imran Ali Rajput, Tajwer Sultana Syed, Arfan Ahmed Gilal, Agha Mushtaque Ahmed, Fahad Nazir Khoso, Ghulam Hussain Abro, Maqsood Anwar Rustamani

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsPink bollwormBt cottonToxicologyPesticideCropBiologyAgronomyHorticultureLarvaBotany

Abstract

fetched live from OpenAlex

The field studies were conducted at the farmer’s field in 2015-2016 to determine the effect of three different insecticides (triazon, radiant and polytrin C) on Bt. and non-Bt. cotton varieties against pink bollworm. The results revealed that triazon was observed the most effective pesticide against PBW on both cotton varieties. The mortality reduction percent of 33.99 to 30.45% was recorded at triazon, 27.72 to 26.95% at radiant and 24.68 to 14.48% at polytrin C respectively, in 2015. However, in 2016 the mortality reduction percent decreased but effective trend of these selected pesticides were observed same with mortality reduction percent of 28.15 to 25.46% at triazon, 21.95 to 23.52% at radiant and 19.96 to 16.37% at polytrin C in Bt. and non-Bt. cotton varieties. In present investigation, triazon was observed the most effective pesticide than radiant and polytrin C on larvae of PBW in both Bt. and non-Bt. varieties.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.262
Teacher spread0.255 · 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 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

Citations4
Published2017
Admission routes1
Has abstractyes

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