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Record W2791208897 · doi:10.1080/19420889.2018.1447743

Deciphering pleiotropy: How complex genes regulate behavior

2018· article· en· W2791208897 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunicative & Integrative Biology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of TorontoCanadian Institute for Advanced Research
Fundersnot available
KeywordsPleiotropyForagingBiologyGenePhenotypeDrosophila melanogasterGeneticsEvolutionary biologyBehavioural geneticsMelanogasterEcology

Abstract

fetched live from OpenAlex

The genetic underpinnings of animal behavior are exceedingly complex. Behavioral phenotypes are commonly regulated by many genes, and the behavioral effects of a gene often dependent on environmental conditions and genetic background. To complicate the study of behavioral genetics further, many genes that regulate behavioral phenotypes are themselves very complex genes, with several gene products and functions. One example of such a complex gene is the foraging gene in D. melanogaster. foraging influences many behaviors in the fruit fly, and the key to its effects likely lies in its complex molecular structure. We've recently found that expression levels of a small subset of transcripts of the foraging gene underlie the behavioral differences seen in adult foraging patterns of the rover and sitter D. melanogaster strains. Here we comment on the larger implications of this and other findings on gene regulation and pleiotropy in behavior.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.786
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.094
GPT teacher head0.319
Teacher spread0.225 · 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