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Record W2805422244 · doi:10.5539/jas.v10n7p503

Synergistic Effect of Phosphine and Carbon Dioxide on the Mortality of Tribolium castaneum (Coleoptera: Tenebrionidae) in Paddy

2018· article· en· W2805422244 on OpenAlexvenueno aff
Ramu Meenatchi, R. P. S. J. Alice, P. P. Paulin

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
FundersScience and Engineering Research BoardMinistry of Food Processing IndustriesDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsFumigationPhosphinePupaCarbon dioxideLarvaToxicologyMoistureBiologyWater contentHorticultureAgronomyChemistryBotanyEcologyBiochemistry

Abstract

fetched live from OpenAlex

Phosphine (PH3) is widely used as a fumigant for the control of stored product pests. Indiscriminate use of PH3 leads to the development of resistant strains. Thus, an experiment was conducted in a laboratory scale fumigation chamber to determine the synergistic effect of carbon dioxide (CO2) and PH3 on the mortality of Tribolium castaneum during fumigation of paddy. PH3 gas generation varies depending upon grain moisture content and dosage of PH3 used for fumigation treatment. Thus, the maximum PH3 concentration with respect to saturation time was achieved when paddy were treated with 98% CO2 + 3 ppmPH3 at 17% moisture content, leading to a quick mortality of different life stages of T. castaneum with minimum LT50 and LT99 value. Among the different stages of T. castaneum, pupal stage was more resistant to all the treatments compared to larva and adult stages. PH3 residues in all the treatments were below the recommended level and it can be considered as safe for consumption.

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 score0.003
Threshold uncertainty score0.007

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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