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Record W6962487814 · doi:10.17632/t658w7twsm

Fatty acids and glycerides are object recognition and carrying cues for foraging Camponotus modoc carpenter ants

2025· dataset· en· W6962487814 on OpenAlexaff

Bibliographic record

VenueMendeley Data · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPerliteForagingPickupGlycerideOleic acid

Abstract

fetched live from OpenAlex

This data set is a supplement to an in review article titled: “Fatty acids and glycerides are object recognition and carrying cues for foraging Camponotus modoc carpenter ants”. Our full description of the methodology, results, and their interpretation can be found in the publication. Abstract from article: "During foraging and nest hygiene maintenance (removal of deceased nestmates), ants recognize objects for pickup and transport based on their surface chemicals. Diverse lipids are present on food items and deceased nestmates of ants, and the lipids oleic acid and 1,2-diolein are already well-known pickup cues. However, the effects of various lipid types on pickup behaviour by ants have not yet been rigorously compared. Using the carpenter ant, Camponotus modoc Wheeler (Hymenoptera: Formicidae), as a model species and pieces of perlite as inert objects for pickup by ants, we (1) compared the effects of fatty acids and glycerides as perlite coating on perlite pickup and transport by ants, (2) tested the effect of 1,2-diolein dose on perlite pickup, and (3) compared pickup behavior by ants in response to pickup cues that are wide-spread (oleic acid and 1,2 diolein), and commercially used in ant baits (soybean oil). Of 18 surface chemicals tested singly as perlite coating, 1,2-diolein, linoleic acid, oleic acid, trilinolenin, and triolein elicited the strongest perlite pickup behaviour. Increasing doses of 1,2-diolein correspondingly enhanced perlite pickup by ants. Oleic acid and 1,2-diolein as perlite coating prompted more perlite pickup by ants than soybean oil. Enriching soybean oil with oleic acid might enhance the pickup efficacy of granular baits by pest ants." We have uploaded our data and scripts as an R studio project. Code used to wrangle data, analyze data and generate plots can be accessed in the project folder by opening the project file. The project contains: ---Data Data files of laboratory experiments to assess ant consumption, colony growth, and mortality to amino acid formulations. ---Outputs Plots and csv files generated from data analysis. ---Scripts Scripts of R code used to wrangle data, conduct analyses, and generate outputs.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.006
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.003
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 head0.107
GPT teacher head0.333
Teacher spread0.226 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueMendeley DataFrench-language works237,207