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Record W2752141223 · doi:10.1038/s41598-017-11516-2

Identification of Genetically Important Individuals of the Rediscovered Floreana Galápagos Giant Tortoise (Chelonoidis elephantopus) Provides Founders for Species Restoration Program

2017· article· en· W2752141223 on OpenAlexaff
Joshua M. Miller, Maud C. Quinzin, Nikos Poulakakis, James P. Gibbs, Luciano B. Beheregaray, Ryan C. Garrick, Michael A. Russello, Claúdio Ciofi, Danielle L. Edwards, Elizabeth A. Hunter, Washington Tapia, Danny Rueda, Jorge Carrión, Andrés A. Valdivieso, Adalgisa Caccone

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersInstitute for Biospheric Studies, Yale UniversityMohamed bin Zayed Species Conservation FundNational Science FoundationYale UniversityBelgian American Educational FoundationGalapagos ConservancyNational Geographic SocietyOak Foundation
KeywordsTortoiseBiologyEcologyZoologyEcosystem

Abstract

fetched live from OpenAlex

Species are being lost at an unprecedented rate due to human-driven environmental changes. The cases in which species declared extinct can be revived are rare. However, here we report that a remote volcano in the Galápagos Islands hosts many giant tortoises with high ancestry from a species previously declared as extinct: Chelonoidis elephantopus or the Floreana tortoise. Of 150 individuals with distinctive morphology sampled from the volcano, genetic analyses revealed that 65 had C. elephantopus ancestry and thirty-two were translocated from the volcano's slopes to a captive breeding center. A genetically informed captive breeding program now being initiated will, over the next decades, return C. elephantopus tortoises to Floreana Island to serve as engineers of the island's ecosystems. Ironically, it was the haphazard translocations by mariners killing tortoises for food centuries ago that created the unique opportunity to revive this "lost" species today.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.336
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.021
GPT teacher head0.266
Teacher spread0.244 · 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

Citations28
Published2017
Admission routes1
Has abstractyes

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