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Record W6967101866 · doi:10.5061/dryad.cz8w9gj42

The genomic consistency of the loss of anadromy in an Arctic fish (Salvelinus alpinus)

2021· dataset· en· W6967101866 on OpenAlexafffundabout

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of VictoriaUniversity of GuelphGovernment of Newfoundland and LabradorDalhousie University
FundersKillam Trusts
KeywordsTubulopathyNucleofectionDiafiltrationHyporeflexiaGestational periodProteogenomics

Abstract

fetched live from OpenAlex

The potentially significant genetic consequences associated with the loss of migratory capacity of diadromous fishes which have become landlocked in freshwater are poorly understood. Consistent selective pressures associated with freshwater residency may drive repeated differentiation both between allopatric landlocked and anadromous populations and within landlocked populations (resulting in sympatric morphs). Alternatively, the strong genetic drift anticipated in isolated landlocked populations could hinder consistent adaptation, limiting genetic parallelism. Understanding the degree of genetic parallelism underlying differentiation has implications for both the predictability of evolution and management practices. We employed an 87k SNP array to examine the genetic characteristics of landlocked and anadromous Arctic Charr (Salvelinus alpinus) populations from five drainages within Labrador, Canada. One gene was detected as an outlier between sympatric, size-differentiated morphs in each of two landlocked lakes. While no single locus differentiated all replicate pairs of landlocked and anadromous populations, several SNPs, genes, and paralogs, were consistently detected as outliers in at least 70% of these pairwise comparisons. A significant C-score suggested the amount of shared outlier SNPs across all paired landlocked and anadromous populations was greater than expected by chance. Our results indicate that despite their isolation, selection due to the loss of diadromy may drive consistent genetic responses in landlocked populations.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.156
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0050.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.311
Teacher spread0.273 · 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.

Study designNot applicable
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

Citations4
Published2021
Admission routes3
Has abstractyes

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