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Record W6948547317 · doi:10.5061/dryad.69p8cz90s

Effect of the Central American Isthmus on gene flow and divergence of the American crocodile Crocodylus acutus

2020· dataset· en· W6948547317 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsMcGill University
Fundersnot available
KeywordsPanamaGene flowTropical Eastern PacificDivergence (linguistics)CrocodileGenetic divergenceGlacial periodPacific oceanLand bridge

Abstract

fetched live from OpenAlex

The final formation of the Central American Isthmus (CAI) about 3.5 Ma altered global ocean circulation, connected North and South America terrestrial biotas and established the Caribbean Sea. The nature of this event creates a natural scenario to test vicariance, divergence, and speciation by allopatry. Studies have shown the effect of the CAI on marine and terrestrial species, but none have examined a large-bodied amphibious taxon. We used RAD sequencing on populations of the American crocodile Crocodylus acutus, to study the genomic variation of C. acutus on both sides of the CAI, infer its demographic history and measure the effect of the opening of the Panama Canal. Our results showed three genomic clusters: 1) Caribbean and the Panama Canal, 2) Pacific coast, and 3) Coiba island. The estimated divergence times between the Caribbean and Pacific populations are about 20 ka, which is two orders of magnitude younger than the formation of the CAI, but coincides with the Last Glacial Maximum. We hypothesize the glacial/interglacial cycles facilitated gene flow between the Caribbean and Pacific crocodile populations after the formation of the CAI, masking any genomic divergence the CAI may have caused. There is no evidence of gene flow associated with the opening of the Panama Canal.

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)0.001
metaresearch head score (Gemma)0.003
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.013
GPT teacher head0.297
Teacher spread0.284 · 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
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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