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Record W2345641585

Speciation in ancient lakes: Insights from the copepods of Sulawesi

2012· article· en· W2345641585 on OpenAlexafffund
James J. Vaillant

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Windsor
FundersDirectorate for Biological SciencesRoyal SocietyMinisterio de Economía y CompetitividadUniversity of Windsor
KeywordsGenetic algorithmGeologyPaleontologyGeographyEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

One of the fundamental questions in biology is the origin of species. Considerable insights into the processes that drive speciation have come from ancient lake systems. In this thesis, I present insights into speciation processes by investigating the species radiations of the ancient Malili Lakes of Sulawesi, Indonesia. The nature of adaptive radiations in the lakes suggests that intraspecific competition for extremely limited resources has driven taxa to adapt to specific habitats and food sources. The copepod populations of Sulawesi reveal that colonization order governs the geographic distribution of zooplankton in freshwater ecosystems. In many Malili Lakes taxa, hybridization between closely related lineages drives diversification, likely by increasing phenotypic diversity within populations. Furthermore, hybridization may be much more common in planktonic taxa than previously thought. Future research in these remarkable habitats is sure to reveal much about the role of hybridization and the origins of biodiversity on earth.

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)0.000
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.014
GPT teacher head0.203
Teacher spread0.190 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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