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Record W4387575764 · doi:10.1016/j.isci.2023.108194

Zebra finches have style: Nest morphology is repeatable and associated with experience

2023· article· en· W4387575764 on OpenAlexafffund
Ben Whittaker, Liam Nolet-Mulholland, Anna Nevoit, Deborah Yun, Connor T. Lambert, Sara C. Blunk, Lauren M. Guillette

Bibliographic record

VenueiScience · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Alberta
FundersWomen and Gender Equality CanadaNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of Alberta
KeywordsNest (protein structural motif)Variation (astronomy)BiologyZoologyEcologyBird nest

Abstract

fetched live from OpenAlex

We investigated whether birds build nests in repeatable styles and, if so, whether styles were associated with past nest-building experience. Laboratory, captive bred zebra finches in an Experimental group were given nest-building experience, whereas, birds in a Control group were not. Each pair (n = 20) then built four nests that underwent image analyses for nest size, geometric shape and entrance orientation. Birds built nests in repeatable styles, with lower morphometric variation among nests built by the same pair and higher morphometric variation among nests built by different pairs. Morphology was not associated with construction time, body weight, nor age of birds. We found lower morphometric variation among nests built by the Experimental group, which also used less material to build nests compared to the Control group. Prior experience may therefore have been advantageous, as learning to reduce material usage while achieving a similar product (nest) may have lowered building costs.

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 categoriesInsufficient payload (model declined to judge)
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 score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.251
Teacher spread0.231 · 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.

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

Citations13
Published2023
Admission routes2
Has abstractyes

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