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Record W7163562967 · doi:10.21199/wb52.4.2

AGE AND SEX INFLUENCE NATAL AND BREEDING DISPERSAL OF PURPLE MARTINS

2021· article· W7163562967 on OpenAlexaboutno aff
Carolyn A. Cook, Glen T. Hvenegaard, Geoffrey L. Holroyd, HARDY PLETZ, Myrna Pearman

Bibliographic record

VenueWestern Birds · 2021
Typearticle
Language
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersPurple Martin Conservation Association
KeywordsBiological dispersalHabitatNest (protein structural motif)SubspeciesPopulationWildlife

Abstract

fetched live from OpenAlex

Dispersal patterns deepen our understanding of population dynamics. Dispersal by all age and sex classes enhances a species’ ability to respond to environmental changes, such as in habitat availability, artificial nest sites, and climate. The migration dynamics of the eastern subspecies of the Purple Martin (Progne subis subis) are well known, but we know less about its patterns of annual dispersal. We compared the frequency, distance, and direction of dispersal by each age/sex cohort of martins in central Alberta, at the northwestern limit of their breeding range. We used two datasets: (1) adult martins banded in central Alberta as nestlings and encountered during the summers of 2017 and 2018, and (2) records of encounters of banded martins in Canada from 1935 to 2016 from the Canadian Wildlife Service’s Bird Banding Office. In Alberta, 36% of birds dispersed from natal sites (by an average distance of 24 km), most commonly to the northeast. Across Canada, 29% of birds dispersed (by an average distance of 183 km), most commonly to the east and northeast. InAlberta, martins at least two years old dispersed less frequently than yearlings since some older martins returned to their natal site after first breeding elsewhere. Dispersal distances of after-second-year martins, which represent natal plus breeding dispersal, were greater than those of second-year birds, which represent natal dispersal alone. Thus some martins continue to disperse after their second year and do not maintain complete fidelity to a breeding site, which is different from our current understanding

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 score0.053
Threshold uncertainty score0.989

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 studies0.0000.001
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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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