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Record W7042761191

Population dynamics of Tribolium castaneum (Herbst) in wheat and wheat mixed with cracked wheat held in different types of containers

2023· dissertation· en· W7042761191 on OpenAlexfundno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2023
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsPopulationWhole wheatMoistureWheat grainWheat flourWater contentWinter wheat
DOInot available

Abstract

fetched live from OpenAlex

The population dynamics of Tribolium castaneum (Herbst), red flour beetle, was studied at 30℃ using long vertical columns (LVCs) (150 mm diameter and 1020 mm long) and shallow containers (SCs) (460 mm long, 660 mm wide, and 150 mm high), containing 14 kg of whole wheat or a diet made of whole wheat and cracked wheat in 19:1 ratio by mass. The moisture content of the wheat or mixed diet was 14.5% (wb). Every 4 weeks and up to 24 weeks the live and dead adults were counted in the SCs or in each section of the LVCs. Each LVC was separated into ten equal sections before removing grain from the LVC. After counting, the grains were incubated at 30℃ and 70% RH for 4 wk, and emerged adults after re-incubation were counted as offspring. The adults and offspring were mainly concentrated in the top section of the LVCs, which could be due to higher mortality in the lower sections and the preference of T. castaneum for the surface of grain bulk. The diet influenced the population, and the insects developed better in the cracked wheat-based diet. The greater surface area of the container increased the multiplication and/ or survival of T. castaneum. Insects inside SCs with larger surface area and with cracked wheat-based diet, had a quicker population increase rate and larger carrying capacity than LVCs.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.930

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 head0.188
Teacher spread0.178 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

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