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Record W2952013694 · doi:10.1038/s41598-019-44038-0

Hybridization between two high Arctic cetaceans confirmed by genomic analysis

2019· article· en· W2952013694 on OpenAlexafffund
Mikkel Skovrind, José Alfredo Samaniego Castruita, James Haile, Eve C. Treadaway, Shyam Gopalakrishnan, Michael V. Westbury, Mads Peter Heide‐Jørgensen, Paul Szpak, Eline D. Lorenzen

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsTrent University
FundersCanada Research ChairsVillum Fonden
KeywordsBelugaBeluga WhaleArcticBiologyZoologyWhaleEvolutionary biologySkullGenomicsPopulationForagingEcologyGenomeGeneticsGeneAnatomyMedicine

Abstract

fetched live from OpenAlex

Abstract In 1990, a skull from a morphologically unusual Monodontid was found in West Greenland and collected for the Natural History Museum of Denmark, University of Copenhagen. From its intermediate morphology, the skull was hypothesized to be a beluga/narwhal hybrid. If confirmed, the specimen would, to our knowledge, represent the sole evidence of hybridization between the only two toothed whale species endemic to the Arctic. Here we present genome-wide DNA sequence data from the specimen and investigate its origin using a genomic reference panel of eight belugas and eight narwhals. Our analyses reveal that the specimen is a male, first-generation hybrid between a female narwhal and a male beluga. We use stable carbon and nitrogen isotope analysis to investigate the dietary niche of the hybrid and find a higher δ13C value than in both belugas and narwhals, suggesting a foraging strategy unlike either parental species. These results further our understanding of the interaction between belugas and narwhals, and underscore the importance of natural history collections in monitoring changes in biodiversity. In addition, our study exemplifies how recent major advances in population genomic analyses using genotype likelihoods can provide key biological and ecological insights from low-coverage data (down to 0.05x).

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)0.001
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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

Citations45
Published2019
Admission routes2
Has abstractyes

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