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Repetitive sequences in phylogeographic inference: a reply to Saltonstall and Lambertini (2012)

2012· article· en· W2120304002 on OpenAlexaff
Joanna R. Freeland, NICOLE VACHON

Bibliographic record

VenueMolecular Ecology Resources · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsTrent University
Fundersnot available
KeywordsBiologyPhylogeographyInferenceEvolutionary biologyMutationGeneticsComputational biologyPhylogeneticsArtificial intelligenceGeneComputer science

Abstract

fetched live from OpenAlex

Abstract In 2011, Vachon and Freeland presented the results of a study that illustrated the importance of considering mutation patterns, including the potential for homoplasy, when deciding whether to include or exclude repetitive sequences from phylogeographic inferences. Saltonstall and Lambertini (2012) criticized this study by suggesting that some of the analyses and interpretations were flawed. In this reply, we explain why we disagree with most of their criticisms and identify some inconsistencies in their analyses. Most importantly, we reiterate the need to examine underlying assumptions, particularly with respect to mutation patterns, when using molecular genetic data to untangle evolutionary relationships.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.607

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 head0.007
GPT teacher head0.241
Teacher spread0.233 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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