MétaCan
Menu
Back to cohort
Record W6967141677 · doi:10.5061/dryad.tmpg4f4zg

Data from: Chemical defense and tonic immobility in early life stages of the Harlequin cabbage bug, Murgantia histrionica (Heteroptera: Pentatomidae)

2021· dataset· en· W6967141677 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsCarleton UniversityUniversity of OttawaMcGill University
Fundersnot available
KeywordsTonic (physiology)JuvenileInstarInsectDefence mechanisms

Abstract

fetched live from OpenAlex

Antipredation strategies are important for the survival and fitness of animals, especially in more vulnerable life stages. In insects, eggs and early juvenile stages are often either immobile or unable to rapidly flee and hide when facing predators. Understanding what alternative antipredation strategies they use, but also how those change over development time, is required to fully appreciate how species have adapted to biotic threats. Murgantia histrionica is a stink bug, conspicuously colored from egg to adult, known to sequester defensive glucosinolates from its cruciferous hosts as adults. We sought to assess whether this chemical defense is also present in its eggs and early nymphal instars and quantified how it fluctuates among life stages. In parallel, we looked at an alternative antipredation strategy, described for the first time in this species: tonic immobility. Our results show that the eggs are significantly more chemically defended than the first two mobile life stages, but not than the third instar. Tonic immobility is also favored by hatchlings, but less so by subsequent instars. We argue the case that over development time, tonic immobility is a useful defensive strategy until adequate chemical protection is achieved over an extended feeding period.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0060.014
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.066
GPT teacher head0.328
Teacher spread0.262 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDFrench-language works237,207