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Record W2568447670 · doi:10.3996/092016-jfwm-075

Feeding Ecology of Brook Silverside, Golden Shiner, and Subyearling Pumpkinseed in a Lake Ontario Embayment

2017· article· en· W2568447670 on OpenAlexaboutno aff
James H. Johnson, Marc A. Chalupnicki, Ross Abbett, Avriel Rose Diaz, Christopher C. Nack

Bibliographic record

VenueJournal of Fish and Wildlife Management · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLepomisBiologyPredationEcologyBenthic zoneInterspecific competitionInvertebrateCentrarchidaeNotropisFisheryFish <Actinopterygii>MicropterusBass (fish)

Abstract

fetched live from OpenAlex

Abstract Fish feeding ecology has been shown to vary over a 24-h period in terms of the prey consumed and feeding intensity. Consequently, in order to best determine the interspecific feeding associations within a fish community, examination of the diet at multiple times over a 24-h period is often necessary. We examined the diel feeding ecology of three fish species that were numerically dominant in a Lake Ontario embayment during summer. The diet of each of the three species, young-of-year Pumpkinseed Lepomis gibbosus, Golden Shiner Notemigonus crysoleucas, and Brook Silverside Labidesthes sicculus, was distinct with no significant overlap in diet composition occurring within any of the 4-h time intervals. The diet composition of each species suggested that Brook Silverside were feeding at the surface (terrestrial invertebrates and aquatic surface dwelling hemipterans), whereas young-of-year Pumpkinseed (amphipods) and Golden Shiner (tipulids) were feeding on different benthic prey. Differences in feeding periodicity were most pronounced for young-of-year Pumpkinseed. Our findings provide valuable insights on interspecific feeding associations among these three fish species during summer in a Lake Ontario embayment.

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 score0.525
Threshold uncertainty score0.955

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 studies0.0010.000
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 head0.011
GPT teacher head0.214
Teacher spread0.204 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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