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Record W2108202493 · doi:10.1007/s00359-009-0422-y

No evidence for melatonin-linked immunoenhancement over the annual cycle of an avian species

2009· article· en· W2108202493 on OpenAlexfundno aff
Deborah M. Buehler, Anita Koolhaas, Thomas J. Van’t Hof, Ingrid Schwabl, Anne Dekinga, Theunis Piersma, B. Irene Tieleman

Bibliographic record

VenueJournal of Comparative Physiology A · 2009
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk OnderzoekRijksuniversiteit Groningen
KeywordsMelatoninAnnual cycleBiologyEcologyZoologyEndocrinology

Abstract

fetched live from OpenAlex

The winter immunoenhancement hypothesis associates long nights and increased exposure to melatonin with enhanced immune function in winter when resource availability is low and the chances of becoming ill are high. Thus, increased exposure to melatonin in the winter could be adaptive for species facing difficult winter conditions. This idea has found some support in studies of resident mammals. In birds, the link between day length and melatonin over the annual cycle is weaker, and contributions of melatonin to seasonal timing are unclear. Furthermore, many species, especially migrants, do not experience the most difficult conditions of their annual cycle in winter. In this study, we tested whether the winter immunoenhancement hypothesis holds in an avian species, the red knot Calidris canutus. We found that melatonin duration and amplitude varied significantly over the annual cycle with the highest values occurring in winter. However, peaks did not correspond to the winter solstice or with annual variation in immune function. Our findings do not support the winter immunoenhancement hypothesis in knots and question whether the idea that immune function should be bolstered in winter can be generalized to systems where winter is not the most difficult time of the year.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.386

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 communication0.0000.001
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 head0.080
GPT teacher head0.364
Teacher spread0.284 · 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 designBench or experimental
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

Citations16
Published2009
Admission routes1
Has abstractyes

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