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Record W2810777870 · doi:10.1642/auk-17-202.1

Ten years tracking the migrations of small landbirds: Lessons learned in the golden age of bio-logging

2018· article· en· W2810777870 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Auk · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBird migrationHabitatEcologyBiologyGeolocationTelemetryTracking (education)GeographyData scienceComputer scienceTelecommunicationsWorld Wide Web

Abstract

fetched live from OpenAlex

In 2007, the first miniature light-level geolocators were deployed on small landbirds, revolutionizing the study of migration. In this paper, we review studies that have used geolocators to track small landbirds with the goal of summarizing research themes and identifying remaining important gaps in understanding. We also highlight research and opportunities using 2 recently developed tracking technologies: archival GPS tags and automated radio-telemetry systems. In our review, we found that most (54%) geolocator studies focused on quantifying natural history of migration, such as identifying migration routes, nonbreeding range, and migration timing. Studies of behavioral ecology (20%) uncovered proximate drivers of movements, including en route habitat quality; that migration routes, but not timing, may be flexible in some species; and different age and sex classes show significant differences in migration strategy. Studies of the evolution of migration (9%) have illustrated that migration is a potential barrier to hybridizing species or subspecies, and some work has correlated gene polymorphisms and methylation patterns with migration behavior. Studies of migratory connectivity (11%) have shown that a moderate level of connectivity is common, although variability across and within species exists. Studies of seasonal interactions (7%) have found mixed results: in some cases, carryover effects have been identified; in other cases, carryover effects are buffered during intervening stages of the annual cycle. Archival GPS tags provide unprecedented precision in locations of nonbreeding sites and migration routes, and will continue to improve understanding of migration across large spatial scales. Automated radio-telemetry systems are revolutionizing our knowledge of migratory stopover biology, and have led to discoveries of previously unknown stopover behaviors. Together, these tracking technologies will continue to provide insight into small migratory landbird movements and contribute important information for conservation of this rapidly declining group.

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.

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)0.001
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 score0.071
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.061
GPT teacher head0.297
Teacher spread0.236 · 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