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Record W2025468763 · doi:10.1139/z02-142

Ontogeny of individual asymmetries in several traits of larval<i>Chironomus riparius</i>Meigen, 1804 (Diptera, Chironomidae)

2002· article· en· W2025468763 on OpenAlexvenueno aff
María J. Servia, Fernando Cobo, Marcos González

Bibliographic record

VenueCanadian Journal of Zoology · 2002
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsnot available
FundersXunta de Galicia
KeywordsChironomus ripariusBiologyFluctuating asymmetryOntogenyInstarChironomidaeLarvaMoultingChironomusZoologyEcology

Abstract

fetched live from OpenAlex

In recent years considerable effort has been dedicated to the analysis of alterations in the morphology of individuals, mainly fluctuating asymmetry, as bioindicators of stress. However, inconsistent results and a general lack of knowledge about the processes involved in the generation and development of asymmetries have discouraged some researchers from using this tool. We present a study of the ontogeny of individual asymmetries in several traits of Chironomus riparius larvae. Development of asymmetries through consecutive instars showed no evidence of sidedness and was in accordance with a compensatory growth model, since growth of the smaller side was typically greater than growth of the larger side during one moult. Surprisingly, however, although growth was compensatory, right–left (R-L) values were size-dependent and increased throughout larval development. Once R-L values were corrected for size dependence, asymmetry levels proved to be similar in all instars except for instar I in one case. We discuss our findings in relation to the developmental patterns and regulation mechanisms described and proposed in similar studies. Specifically, the coincidence of our results with those of another study on insects may indicate the existence of similar regulatory systems throughout this group of animals.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.247
Teacher spread0.201 · 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 designObservational
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

Citations17
Published2002
Admission routes1
Has abstractyes

Explore more

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