MétaCan
Menu
Back to cohort
Record W2960770319 · doi:10.1111/gbb.12598

Social behavior and aging: A fly model

2019· review· en· W2960770319 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGenes Brain & Behavior · 2019
Typereview
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsYork UniversityWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLongevityTransgenerational epigeneticsAutismSchizophrenia (object-oriented programming)PsychologyInheritance (genetic algorithm)Drosophila melanogasterDevelopmental psychologyNeuroscienceBiologyPsychiatryGeneticsOffspring

Abstract

fetched live from OpenAlex

The field of behavioral genetics has recently begun to explore the effect of age on social behaviors. Such studies are particularly important, as certain neuropsychiatric disorders with abnormal social interactions, like autism and schizophrenia, have been linked to older parents. Appropriate social interaction can also have a positive impact on longevity, and is associated with successful aging in humans. Currently, there are few genetic models for understanding the effect of aging on social behavior and its potential transgenerational inheritance. The fly is emerging as a powerful model for identifying the basic molecular mechanisms underlying neurological and neuropsychiatric disorders. In this review, we discuss these recent advancements, with a focus on how studies in Drosophila melanogaster have provided insight into the effect of aging on aspects of social behavior, including across generations.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.225
GPT teacher head0.437
Teacher spread0.212 · 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