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Record W2152085343 · doi:10.1139/z00-033

Health impact of phytohaemagglutinin-induced immune challenge on great tit (<i>Parus major</i>) nestlings

2000· article· en· W2152085343 on OpenAlexvenueno aff
Peeter Hõrak, I. Ots, Lea Tegelmann, Anders Pape Møller

Bibliographic record

VenueCanadian Journal of Zoology · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersUppsala UniversitetEesti Teadusfondi
KeywordsBiologyPhytohaemagglutininParusImmune systemOrganismImmunologyImmunityImmunocompetenceLymphocyteEcologyZoologyGenetics

Abstract

fetched live from OpenAlex

Assuming that immune function is resource-limited, it can be expected to compete with other important functions of an organism for the total resource pool, giving rise to trade-offs in resource allocation. To test whether such a trade-off exists between immune defence and growth, the physiological impact of an immune challenge was examined in great tit (Parus major) nestlings, using phytohaemagglutinin (PHA) as a novel antigen. Nestlings injected intradermally with PHA in wing webs at 8 days of age produced a heterophilic response, while their growth was not suppressed in comparison with untreated control siblings. Nestlings that grew poorly produced a weaker cutaneous response to PHA inoculation than well-growing nestlings. These two results suggest that the response to PHA (a measure of the intensity of T-lymphocyte mediated immune responsiveness) is resource demanding, but these resources are not reallocated from those used for growth. This finding can be reconciled with current hypotheses, which propose that the currency in trade-offs between immune response and other demands on the organism is not necessarily energy or macronutrients but may instead be based on immunopathology, carotenoids, or production of free radicals.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.260
Teacher spread0.229 · 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

Citations25
Published2000
Admission routes1
Has abstractyes

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