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Record W2003563200 · doi:10.3791/50069

<em>C. elegans</em> Chemotaxis Assay

2013· article· en· W2003563200 on OpenAlexafffund
Olivia Margie, Christopher P. Palmer, Ian D. Chin-Sang

Bibliographic record

VenueJournal of Visualized Experiments · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsQueen's University
FundersQueen's University
KeywordsChemotaxisEquidistantCaenorhabditis elegansPetri dishBiologyComputer scienceBiological systemMathematicsGeometryGenetics

Abstract

fetched live from OpenAlex

Many organisms use chemotaxis to seek out food sources, avoid noxious substances, and find mates. Caenorhabditis elegans has impressive chemotaxis behavior. The premise behind testing the response of the worms to an odorant is to place them in an area and observe the movement evoked in response to an odorant. Even with the many available assays, optimizing worm starting location relative to both the control and test areas, while minimizing the interaction of worms with each other, while maintaining a significant sample size remains a work in progress (1-10). The method described here aims to address these issues by modifying the assay developed by Bargmann et al.(1). A Petri dish is divided into four quadrants, two opposite quadrants marked "Test" and two are designated "Control". Anesthetic is placed in all test and control sites. The worms are placed in the center of the plate with a circle marked around the origin to ensure that non-motile worms will be ignored. Utilizing a four-quadrant system rather than one 2 or two 1 eliminates bias in the movement of the worms, as they are equidistant from test and control samples, regardless of which side of the origin they began. This circumvents the problem of worms being forced to travel through a cluster of other worms to respond to an odorant, which can delay worms or force them to take a more circuitous route, yielding an incorrect interpretation of their intended path. This method also shows practical advantages by having a larger sample size and allowing the researcher to run the assay unattended and score the worms once the allotted time has expired.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.019

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 head0.015
GPT teacher head0.326
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations160
Published2013
Admission routes2
Has abstractyes

Explore more

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