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Shape of Single and Multiple Central-Place Territories in a Stream-Dwelling Fish

2011· article· en· W1779597981 on OpenAlexafffund
Stefán Ó. Steingrímsson, James W. A. Grant

Bibliographic record

VenueEthology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaConcordia University
KeywordsForagingPredationRange (aeronautics)GeographyFish <Actinopterygii>EcologyFisheryBiology

Abstract

fetched live from OpenAlex

Territory shape yields important insights into how animals exploit local resources. Territories of stream-dwelling salmonids are typically (1) mapped around a single central-place, (2) described as circular, elliptical or teardrop-shaped, and (3) believed to reflect their exploitation of drifting invertebrate prey. In this study, we tested the current view of territory shape by mapping multiple central-place territories for 50 young-of-the-year Atlantic salmon. Multiple central-place areas were more elongated (eccentricity: median = 1.301, range = 1.043–2.784) than the foraging patterns around each central place (eccentricity: median = 1.135, range = 1.014–1.385). In addition, multiple central-place areas were elongated along the stream length (33 of 50 fish), whereas the foraging areas around each station tended to be elongated along the stream width (32 of 50 fish). These findings may be explained by the way that stream salmonids interact with drifting prey. At each central place, a wider foraging area should provide an increased access to prey drifting downstream. Similarly, by regularly patrolling a large multiple central-place area along the stream axis, a territorial fish may increase its access to drifting prey by excluding competitors from upstream areas. Further studies are needed on the ecological factors that determine territory shape in stream fish and multiple central-place foragers.

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 score0.013
Threshold uncertainty score0.748

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 head0.024
GPT teacher head0.219
Teacher spread0.194 · 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

Citations3
Published2011
Admission routes2
Has abstractyes

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