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Record W2150217905 · doi:10.1111/jav.00612

Visual obstruction and vigilance: a natural experiment

2015· article· en· W2150217905 on OpenAlexaff
Guy Beauchamp

Bibliographic record

VenueJournal of Avian Biology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsVigilance (psychology)CalidrisPredationBiologyForagingPredatorALARMEcologyVisual perceptionZoologyPerceptionNeuroscience

Abstract

fetched live from OpenAlex

Visual obstructions can cause an increase in antipredator vigilance in prey animals by making predator detection more difficult. However, visual obstructions can also skew the perception of group size and inter‐individual distances and impair the detection of alarm signals by conspecifics. These changes within the group alone can cause an increase in vigilance. To disentangle the contribution of these various factors to changes in vigilance, I documented vigilance in a gregarious species, the semipalmated sandpiper Calidris pusilla , foraging in a habitat where a naturally‐occurring visual barrier partially prevented predator detection without altering the transfer of information about predation risk within the group. I used a matched sampling design to collect vigilance data for birds using adjacent areas with and without the visual barrier. In the visually‐obstructed area, sandpipers maintained a higher level of vigilance, occurred farther away from cover and in smaller flocks, and preferentially scanned the area of danger with one eye in particular. All these changes suggest that visual obstruction increased perceived predation risk. I conclude that it is the inability to get a good view of any approaching predator, rather than changes in intra‐group communication that caused the increase in vigilance in the visually‐obstructed area.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score0.074

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 head0.032
GPT teacher head0.292
Teacher spread0.259 · 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

Citations27
Published2015
Admission routes1
Has abstractyes

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