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Record W4242513186 · doi:10.1093/condor/108.4.877

Isotopic Evaluation of Interrupted Molt in Northern Breeding Populations of the Loggerhead Shrike

2006· article· en· W4242513186 on OpenAlexaffabout
Guillermo E. Pérez, Keith A. Hobson

Bibliographic record

VenueOrnithological Applications · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsFeatherShrikeFlight featherMoultingEcologyLatitudeZoologyBiologyGeographyFisheryHabitat

Abstract

fetched live from OpenAlex

Abstract Abstract The Loggerhead Shrike (Laniusludovicianus) breedsthroughout North America and various populationsapparently exhibit diverse molt strategies.However, molt in this species and how it may varygeographically is generally poorly known. Weinvestigated molt sequence in 27 breedingLoggerhead Shrikes using stable hydrogen(δD) isotope analysis of flightfeathers. Because feather δD varies with thelatitude at which feathers are grown in NorthAmerica, it is relatively straightforward toidentify those feathers grown south of anindividual's breeding location. We sampled 11feathers per individual to evaluate locations offeather molt between breeding and wintering groundsin North America. Sampling took place in centralSaskatchewan, Canada (n = 18 individuals) andin the southern region of the Saskatchewan-Manitobaborder (n = 9). We found evidencethat shrikes initiated flight feather molt on theirbreeding grounds (P1 and P3) but thenlargely suspended molt until reaching theirwintering areas. The isotopic evidence suggeststhat the first primary (P1, most depleted indeuterium, mean = −103‰) provides information onshrike breeding latitudes while the innermosttertial (S9, most enriched in deuterium, mean = −49‰)provides information on shrike wintering orsouthernmost molting latitudes.

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 score0.018
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.042
GPT teacher head0.297
Teacher spread0.255 · 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

Citations9
Published2006
Admission routes2
Has abstractyes

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