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Record W7079514396 · doi:10.26108/k9pd-cd75

Nest feathering by tree swallows (Tachycineta bicolor) in response to artificial warming

2014· article· en· W7079514396 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2014
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsFeatherNest (protein structural motif)Nova scotiaNest boxFacultativeFlight featherPasser

Abstract

fetched live from OpenAlex

Bird nests protect eggs, developing young, and incubating adults from inclement weather and predation. In Tree Swallows (Tachycineta bicolor) females are solely responsible for incubating eggs. Prior to and while females are incubating, males compete with rivals for feathers that they use to line nests. The thermal benefits hypothesis proposes that this is because maintenance of proper egg temperatures is critical. I tested the thermal benefits hypothesis: I predicted that artificially heating Tree Swallow nests would result in addition of fewer feathers. I quantified feathers from Tree Swallow nests in the Annapolis Valley, Nova Scotia, and St. Denis, Saskatchewan. Nesting started the first week of May and continued into mid June. At both locations nests were randomly assigned to control or experimental treatments. In Nova Scotia wire platforms were added under nests early in nest-building so that later manipulations would cause reduced disturbance. Experimental nests had 24h heating pads (spent pads were used for controls) placed under them that were replaced daily until culmination of incubation. Contrary to the thermal benefits hypothesis, there was no statistically significant difference in feather numbers between control and experimental nests. However, nests initiated earlier in the season had significantly more feathers than those initiated later in the season. Further studies will have to be conducted to determine if feather addition is also facultative in response to other variables. Key words: artificial heating, nest feathering, Tachycineta bicolor, Tree Swallow.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.013
GPT teacher head0.232
Teacher spread0.218 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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