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Record W2031570587 · doi:10.1139/z04-066

The effects of crayfish predation on phenotypic and life-history variation in fathead minnows

2004· article· en· W2031570587 on OpenAlexfundvenueno aff
Robin C. Kusch, Douglas P. Chivers

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMinnowBiologyPimephales promelasCrayfishHatchingHatchlingPredationPredatorZoologyEcologyReproductionCyprinidaeFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Ecological theory predicts that the timing of the transition between life-history stages should vary with the costs and benefits associated with each stage. For example, the timing of hatching or metamorphosis may vary with the predation risk in each stage. Predator-induced changes in hatching time are well documented in some taxa but have not been reported in fishes. We provide the first empirical evidence that a species of fish can alter its hatching time in response to predator cues. We showed that fathead minnows, Pimephales promelas Rafinesque, 1820, exposed to chemical cues from virile crayfish, Orconectes virilis (Hagen, 1870), foraging on minnow embryos hatch sooner than those exposed to a blank control. Moreover, in the presence of cues from virile crayfish feeding on minnow embryos, the hatchlings exhibited a change in morphology because they had significantly shorter total lengths. There was a significant positive correlation between hatchling size and length of the developmental period, except in the high predation threat treatment. By hatching earlier, the fathead minnows escaped predation from virile crayfish that were actively foraging on fathead minnow eggs. Hatching at a smaller size, however, may make the fry more vulnerable to other predators.

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)0.001
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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

Citations57
Published2004
Admission routes2
Has abstractyes

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