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Record W2115840866 · doi:10.1139/z03-177

Does living in streams with fish involve a cost of induced morphological defences?

2003· article· en· W2115840866 on OpenAlexvenueno aff
Jonas Dahl, Barbara L. Peckarsky

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsSTREAMSBiologySalvelinusTroutFontinalisPredationMayflyFish <Actinopterygii>ZoologyEcologyLarvaFishery

Abstract

fetched live from OpenAlex

Previous studies have shown that chemical cues from brook trout (Salvelinus fontinalis) induce relatively longer caudal filaments and heavier exoskeletons in the mayfly Drunella coloradensis. These characters constitute morphological defences that reduce larval mortality from brook trout predation. There is also a potential fitness cost of living in streams with trout, as D. coloradensis females emerge at smaller sizes from streams with fish compared with females in streams without fish. In this study, we obtained additional data to evaluate the hypothesis that these costs of living in streams with fish could be attributed to inducible defences. A field survey of seven different streams showed that mature (black wing pad) female larvae from streams with fish invested a smaller proportion of their body mass in eggs than females maturing in streams without fish. Furthermore, a negative relationship between female allocation to eggs and to morphological defence characters (relative length of the caudal filament) provides evidence of a cost of inducible defences in this species.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.200
Teacher spread0.187 · 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 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

Citations5
Published2003
Admission routes1
Has abstractyes

Explore more

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