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Record W2107904679 · doi:10.1139/f01-060

Prey size of salmonid fishes in streams, lakes, and oceans

2001· article· en· W2107904679 on OpenAlexafffundvenue
Ernest R. Keeley, James WA Grant

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPredationSTREAMSInvertebrateHabitatBiologyEcologySalmonidaeNicheFish <Actinopterygii>Ecological nicheHydrobiologyFisheryAquatic environmentSalmo

Abstract

fetched live from OpenAlex

The growth rate of salmonid fishes is typically fastest in oceans, intermediate in lakes, and slowest in streams. We compiled literature data to test whether differences in the size of prey eaten by salmonids in the three habitats could account for these differences in growth rate (i.e., the prey-size hypothesis). In all three habitats, salmonid fishes exhibited ontogenetic niche shifts from feeding primarily on invertebrates when small to feeding on fishes when large. Contrary to the prey-size hypothesis, invertebrates eaten in streams were larger than those eaten in lakes or oceans, whereas fish eaten in oceans were smaller than those eaten in streams or lakes. Consistent with the prey-size hypothesis, salmonids began eating fish at a smaller size in oceans (8 cm) than in lakes (15 cm) or streams (27 cm). However, the size at which salmonids became predominantly piscivorous (31 cm) did not differ significantly between habitats. We suggest that the difference in growth potential between the three habitats is partly related to the size at which fish first enter the diet.

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 score0.416
Threshold uncertainty score0.652

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 studies0.0000.001
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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

Citations181
Published2001
Admission routes3
Has abstractyes

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