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Record W3158754502

Pair Movements in Canada Geese

2021· article· en· W3158754502 on OpenAlexaboutno aff
Kathryn Wilkins

Bibliographic record

VenueProceedings of Student Research and Creative Inquiry Day · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsFlockPhilopatryBroodFledgeBrantaGooseGeographySeasonal breederFlight featherNest (protein structural motif)EcologyWaterfowlBiologyAnatidaeBiological dispersalZoologyFisheryDemographyMoultingHatchingLarvaHabitat
DOInot available

Abstract

fetched live from OpenAlex

Canada geese (Branta canadensis) are a staple of most parks, neighborhoods, and even shopping centers (Conover 1998) – wherever there is a body of water with subsequent aquatic vegetation, you will most likely find Canada geese. This is especially true during their annual molting period from mid-June to late July, in which they shed and regrow their flight feathers. It is generally accepted that geese with broods prefer to molt and rear the brood near to or at their own birthplaces- this concept is known as philopatry. Over the summer of 2020, I observed the Canada goose flock of Cookeville, Tennessee to discern whether this philopatric trend can be observed within the flock. Geese with broods and those without were examined and analyzed separately to accommodate for the heightened philopatry that is commonly seen in geese that are rearing broods. Results showed that local males, those first captured in the Cookeville flock as hatch years, did indeed travel farther on average than local females. It was also found that individuals were philopatric to their natal sight whether or not they had had a brood that season. Such results raise questions regarding the following, or lack thereof, of seen trends within the study: (1) If the trends followed are seen in the Cookeville flock, are they followed by other resident flocks? and (2) Are the common trends that are not being followed due to the flock being a resident flock, or is it due to other variables?

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.876

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 communication0.0000.000
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 head0.138
GPT teacher head0.362
Teacher spread0.224 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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