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Do male and female black‐backed woodpeckers respond differently to gaps in habitat?

2010· article· en· W2001658851 on OpenAlexaffabout
Jennifer C. Pierson, Fred W. Allendorf, Victoria A. Saab, Pierre Drapeau, Michael K. Schwartz

Bibliographic record

VenueEvolutionary Applications · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversité du Québec à Montréal
FundersU.S. Forest ServiceAmerican Association of University WomenPhilanthropic Educational OrganizationNational Science FoundationNorthwest Scientific AssociationUniversity of Montana
KeywordsBiologyEcologyHabitatTaigaPopulationGene flowBorealBiological dispersalEffective population sizeGenetic diversityDemography

Abstract

fetched live from OpenAlex

We used population- and individual-based genetic approaches to assess barriers to movement in black-backed woodpeckers (Picoides arcticus), a fire-specialist that mainly occupies the boreal forest in North America. We tested if male and female woodpeckers exhibited the same movement patterns using both spatially implicit and explicit genetic analyses to define population structure and movement patterns of both sexes among populations. Three genetic groups were identified, a large, genetically continuous population that spans from the Rocky Mountains to Quebec, a small isolated population in South Dakota and a separate population in the western portion of their distribution (Oregon). Patterns of genetic diversity suggest extensive gene flow mediated by both males and females within the continuous boreal forest. However, male-mediated gene flow is the main form of connectivity between the continuously distributed group and the smaller populations of South Dakota and Oregon that are separated by large areas of unforested habitat, which apparently serves as a barrier to movement of female woodpeckers.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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

Citations33
Published2010
Admission routes2
Has abstractyes

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