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Record W7071676121

Synergistic effect of carbon monoxide mixed with carbon dioxide in air on mortality of stored-grain insects

2008· dissertation· en· W7071676121 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2008
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsSitophilusCarbon monoxideCarbon dioxideWeevilRice weevilGranaryPEST analysis
DOInot available

Abstract

fetched live from OpenAlex

Rusty grain beetle, cryptorestes ferrugineus (stephens), red flour beetre, Triborium castaneum (Herbst), and granary weevil, sitophilus granarius (L.), are dominant stored- grain pest species in canada.A study to determine the effect of carbon monoxide (co) mixed with carbon dioxide (cor) in air on controlling stored-grain insects was conducted in the laboratory.within modified airtight gas exposure systems, mixed-age adults of rusty $ain beetle, red flour beetle, and granary weevil in tough wheat with moisture content of 15% were exposed for 48, 96, 144 and 192 h to three types of gas mixtures in air,5o/o CO,30% CO2, and 5% CO +30vo COzat2l C and 30oC, the balance of the gases being air, carbon monoxide alone had no effect on mortality of the three insect adults.For c. ferrugineus, there was no difference in mortality between by co2 alone and co2 + co mixture at either temperature for all exposures.However, both T. casaneum and s.granarius had higher mortality in the CO2 + CO mixture than the CO2 alone at both temperatures.Moreover, S. granarius was more susceptible to CO2 + CO mixture than Z castaneum.These results suggest that for cefiain species co could be used to increase the efficiency of co2, especially at high temperature.Inhibition by co to electron transport chain at the cellular level is presumed to exelt synergistic influence on inducing greater mortality of some insects under CO2 stress.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.185
Teacher spread0.176 · 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 teacher head, 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

Citations0
Published2008
Admission routes1
Has abstractyes

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