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Record W2108310535 · doi:10.1139/z05-136

Specialization and development of beach hunting, a rare foraging behavior, by wild bottlenose dolphins (<i>Tursiops</i> sp.)

2005· article· en· W2108310535 on OpenAlexvenueno aff
Brooke L. Sargeant, Janet Mann, Per Berggren, Michael Krützen

Bibliographic record

VenueCanadian Journal of Zoology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsForagingBottlenose dolphinBayHabitatBiologyEcologyFisheryShoreCetaceaGeography

Abstract

fetched live from OpenAlex

Foraging behaviors of bottlenose dolphins vary within and among populations, but few studies attempt to address the causes of individual variation in foraging behavior. We examined how ecological, social, and developmental factors relate to the use of a rare foraging tactic by wild bottlenose dolphins (Tursiops sp. Gervais, 1855) in Shark Bay, Western Australia. Beach hunting involves partial and nearly complete stranding on beach shores. Over 10 years of observation, only four adults and their calves were observed beach hunting in more than 1 year. Of two adult beach hunters observed in detail, one was more specialized in beach hunting than the other, indicating substantial flexibility in degree of use. Only calves born to beach hunters developed the tactic, although complete stranding was not observed at least up to 5 years of age. Beach hunters used shallow, inshore habitats significantly more than others and were more likely to hunt during incoming tide. Mitochondrial DNA haplotypes were not consistent with strict matrilineal transmission. Thus, beach hunting likely involves vertical social learning by calves, while individual, horizontal, and (or) oblique learning may occur among individuals who frequent coastal habitats.

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 score0.337
Threshold uncertainty score0.999

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)0.0010.000

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 head0.013
GPT teacher head0.222
Teacher spread0.208 · 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

Citations152
Published2005
Admission routes1
Has abstractyes

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