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Record W2106238415 · doi:10.1093/beheco/arp059

Alternative foraging tactics and risk taking in brook charr (Salvelinus fontinalis)

2009· article· en· W2106238415 on OpenAlexaff
Michelle Farwell, Robert L. McLaughlin

Bibliographic record

VenueBehavioral Ecology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFontinalisSalvelinusForagingPredationBiologyEcologyOptimal foraging theoryFisheryZoologyDemographyTroutFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Recently emerged brook charr (Salvelinus fontinalis) foraging in still-water pools along the sides of streams tend to be sedentary, feeding from the lower portion of the water column (sitting and waiting), or active, feeding from the upper portion of the water column (active search). Individuals exhibiting intermediate behavior are observed less frequently. We assessed the perceptual, energetic, and locomotor bases of the individual differences in foraging tactics by testing whether an individual's activity while searching for prey in the field was linked to its willingness to take risks, resting metabolic rate (RMR), and swimming capacity. Proportion of time an individual spent moving during prey search was quantified in the field, the individual was captured, and willingness to take risks (field), resting oxygen consumption (lab), and locomotor ability (lab) were measured. Individuals that spent a lesser proportion of time moving in the field took longer to exit from a dark tube into an unfamiliar field environment, and delayed their exit times more in response to a novel object, than did individuals that spent a greater proportion of time moving in the field. Proportion of time spent moving in the field was unrelated to resting oxygen consumption and swimming capacity measured in the laboratory. Dispositions in foraging behavior and risk taking early in life could influence encounter rates with novel prey and habitats, which are important steps in the initial stages of resource polymorphisms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.019
GPT teacher head0.285
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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

Citations68
Published2009
Admission routes1
Has abstractyes

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