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A test of ecological selection against young‐of‐the‐year hybrids of sympatric sticklebacks

2000· article· en· W2057774622 on OpenAlexaff
Steven M. Vamosi, Todd Hatfield, Dolph Schluter

Bibliographic record

VenueJournal of Fish Biology · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologySympatric speciationSelection (genetic algorithm)HybridEcologyTest (biology)FisheryZoologyArtificial intelligence

Abstract

fetched live from OpenAlex

Ecological selection against hybrids, the reduction in hybrid fitness attributed solely to environmental factors, was tested by introducing young‐of‐the‐year benthic, limnetic and F 1 hybrid sticklebacks Gasterosteus aculeatus to divided experimental ponds and lake enclosures. The frequency of hybrids in samples taken at the end was significantly lower than their frequency at introduction. Hybrid survival was significantly lower in pond‐sides in which they were initially the most common cross type than in pond‐sides in which they were initially rare, suggesting that hybrid survival may be frequency‐dependent. Growth rate of F 1 hybrids was marginally lower than benthic growth rates, being significantly lower than in ponds and not different in lake enclosures. The diet of hybrids overlapped with both parent species in ponds and with benthic diets in lake enclosures. The results suggest that ecological selection is acting against young‐of‐the‐year hybrid sticklebacks.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.011
GPT teacher head0.221
Teacher spread0.209 · 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.

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

Citations59
Published2000
Admission routes1
Has abstractyes

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