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Record W4401990088 · doi:10.1126/science.adn2573

Architectural traditions in the structures built by cooperative weaver birds

2024· article· en· W4401990088 on OpenAlexafffund
Maria C. Tello-Ramos, Lucy Harper, Isabella Tortora-Brayda, Lauren M. Guillette, Pablo Capilla‐Lasheras, Xavier A. Harrison, Andrew J. Young, Susan D. Healy

Bibliographic record

VenueScience · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Alberta
FundersNatural Environment Research CouncilNatural Sciences and Engineering Research Council of CanadaBiotechnology and Biological Sciences Research CouncilTempleton World Charity FoundationCanada Research ChairsDirectorate for Biological SciencesUniversity of PretoriaUniversity of St AndrewsNational Geographic Society
KeywordsBiologyEvolutionary biologyZoology

Abstract

fetched live from OpenAlex

Humans cooperate to build complex structures with culture-specific architectural styles. However, they are not the only animals to build complex structures nor to have culture. We show that social groups of white-browed sparrow weavers ( Plocepasser mahali ) build structures (nests for breeding and multiple single-occupant roosts for sleeping) that differ architecturally among groups. Morphological differences are consistent across years and are clear even among groups with territories a few meters apart. These repeatable differences are not explained by among-group variation in local weather conditions, bird size, tree height, or patterns of genetic relatedness. Architectural styles are also robust to the immigration of birds from other groups.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.027
GPT teacher head0.272
Teacher spread0.245 · 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

Citations29
Published2024
Admission routes2
Has abstractyes

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