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Record W4405431050 · doi:10.1139/cjz-2024-0085

Population genetics of <i>Salvator merianae</i> (Reptilia, Teiidae) in its southernmost distribution

2024· article· en· W4405431050 on OpenAlexvenueno aff
Carolina Imhoff, Matthew H. Shirley, Federico Giri, Gualberto Pacheco‐Sierra, Pablo Siroski, Patricia Susana Amavet

Bibliographic record

VenueCanadian Journal of Zoology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsTeiidaeBiologyPopulationPopulation geneticsEcologyZoologyLizardSauriaDemography

Abstract

fetched live from OpenAlex

The black and white tegu ( Salvator merianae Duméril and Bibron, 1839) is the most widespread lizard species in the southern part of South America. This is an important species as a natural resource, traditionally used for food and traded as leather and pets, and this intensive exploitation can be important for regional economies in their range. We analyzed their genetic diversity, structure, and mating system in Argentina using the mitochondrial ND4 locus and 10 microsatellite loci. We hypothesized low genetic diversity, high levels of interpopulation structure, and multiple paternal contribution to clutches. Our results support our hypotheses, detecting two divergent mitochondrial haplogroups, low levels of allelic diversity and low to medium population structure values using microsatellites, and that S. merianae is both polygynous and has multiple paternal contributions to the clutches we analyzed. These results are informative for the on-going sustainable use-based management of S. merianae, ensuring the sustainability of its commercially exploited populations and the habitats on which they depend.

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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.228
Teacher spread0.213 · 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
Published2024
Admission routes1
Has abstractyes

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