MétaCan
Menu
Back to cohort
Record W2338184411 · doi:10.3791/53980

Foraging Path-length Protocol for <em>Drosophila melanogaster</em> Larvae

2016· article· en· W2338184411 on OpenAlexafffund
Ina Anreiter, Oscar Vasquez, Aaron M. Allen, Marla B. Sokolowski

Bibliographic record

VenueJournal of Visualized Experiments · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsForagingDrosophila melanogasterLarvaBiologyTraitPhenotypic plasticityPath analysis (statistics)Path (computing)GeneticsEcologyGeneComputer scienceMachine learning

Abstract

fetched live from OpenAlex

The Drosophila melanogaster larval path-length phenotype is an established measure used to study the genetic and environmental contributions to behavioral variation. The larval path-length assay was developed to measure individual differences in foraging behavior that were later linked to the foraging gene. Larval path-length is an easily scored trait that facilitates the collection of large sample sizes, at minimal cost, for genetic screens. Here we provide a detailed description of the current protocol for the larval path-length assay first used by Sokolowski. The protocol details how to reproducibly handle test animals, perform the behavioral assay and analyze the data. An example of how the assay can be used to measure behavioral plasticity in response to environmental change, by manipulating feeding environment prior to performing the assay, is also provided. Finally, appropriate test design as well as environmental factors that can modify larval path-length such as food quality, developmental age and day effects are discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.068
GPT teacher head0.431
Teacher spread0.364 · 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 designBench or experimental
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

Citations18
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Visualized ExperimentsSame topicNeurobiology and Insect Physiology ResearchFrench-language works237,207