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Record W2996568888 · doi:10.14430/arctic69301

Diversity and Keratin Degrading Ability of Fungi Isolated from Canadian Arctic Marine Bird Feathers

2019· article· en· W2996568888 on OpenAlexafffundvenueabout
Brent M. Robicheau, Sarah J. Adams, Jennifer F. Provencher, Gregory J. Robertson, Mark L. Mallory, Allison K. Walker

Bibliographic record

VenueARCTIC · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsEnvironment and Climate Change CanadaAcadia UniversityDalhousie University
FundersEnvironment and Climate Change CanadaGénome QuébecAssociation of Canadian Universities for Northern StudiesNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsEiderFeatherBiologyLarusArcticZoologyEcologyFlight featherFisheryMoulting

Abstract

fetched live from OpenAlex

We present the first records of fungi associated with feathers from seabirds and sea ducks in the Canadian Arctic and sub-Arctic. Birds sampled in Nunavut and Newfoundland (Canada) included the Common Eider (Somateria mollissima), King Eider (S. spectabilis), Black-legged Kittiwake (Rissa tridactyla), Northern Fulmar (Fulmarus glacialis), Glaucous Gull (Larus hyperboreus), Black Guillemot (Cepphus grylle), and Thick-billed Murre (Uria lomvia). In total 19 fungal species were cultured from feathers, identified using ITS rDNA barcoding, and screened for their ability to degrade keratin using a keratin azure assay. Our results indicate that 1) of the 19 isolates, 74% were ascomycetes, while the remaining 26% were basidiomycetes (yeasts); 2) 21% of the ascomycete isolates demonstrated keratinolytic activity (a known pathogenicity factor for fungi that may potentially be harmful to birds); 3) the largest number of fungi were cultured from the sampled Thick-billed Murre; and 4) based on a multiple correspondence analysis, there is some indication that both the King Eider and the Thick-billed Murre collected in the low Arctic had distinct fungal communities that were different from each other and from the other birds sampled. Although our sample sizes were small, initial trends in point (4) do demonstrate that additional study is merited to assess whether the fungal community differences are influenced by variation in the known ecologies of the avian hosts and fungi identified.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.138
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.194
Teacher spread0.187 · 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

Citations6
Published2019
Admission routes4
Has abstractyes

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