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Record W7048029967

Inbreeding Affects on Beetle Clustering

2018· article· en· W7048029967 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueK-State Research Exchange (Kansas State University) · 2018
Typearticle
Languageen
FieldEngineering
TopicPhotocathodes and Microchannel Plates
Canadian institutionsnot available
Fundersnot available
KeywordsRed flour beetleInbreedingPEST analysisFecundityCluster analysisAttractionStrain (injury)
DOInot available

Abstract

fetched live from OpenAlex

The Red Flour Beetle (Tribolium castaneum; Coleoptera: Tenebrionidae) is a common pest in many grain mills (Baldwin and Fasulo 2010) and found wherever grains or other dried foods are stored (Schröder 2008). The Red Flour Beetle ”facilitates genetic analysis with ease of culture, a short life cycle, high fecundity and facility for genetic crosses, allowing efficient genetic screens (Schröder 2008).” This can allow for them to have a strong genetic code the longer that they are bred in the lab. So, for this experiment we will be trying to see what affect inbreeding has on the aggregation behavior in the Red Flour Beetle. The purpose of this experiment is to see how genetic background influences grouping behavior. Two different strains of Tribolium castaneum were used in this experiment. The one strain used was the Hudson Red Flour Beetle which originates from Hudson, Kansas. They have been bred in the lab for 10 years. The other beetle that was used is the NDG Red Flour Beetle, which originates from Manitoba, Canada and has been in the lab 30 years. After completing this experiment, our findings are that the Hudson are considerably more light sensitive than the Hudson and as soon as light hit them they become very active. There was a noticeably higher percentage of NDG beetles that would cluster together and when they clustered they only clustered with their own strain. This leads us to believe that the NDG beetles have stronger aggregation behavior due to the significant amount of time they have been in lab breeding, compared to the Hudson beetle. The inbreeding that occurred might of allowed for the beetles to develop a more similar genetic code that allows them to group together more easily.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.276
Teacher spread0.223 · 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