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Record W1996867871 · doi:10.1080/08997659.2012.675934

Correlation of Parasites with Growth of Yellow Perch

2012· article· en· W1996867871 on OpenAlexaff
Véronique B. Cloutier, Hélène Glémet, Bastien Ferland‐Raymond, Andrée D. Gendron, David J. Marcogliese

Bibliographic record

VenueJournal of Aquatic Animal Health · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsEnvironment and Climate Change CanadaUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsBiologyPerchCorrelationZoologyPositive correlationFish <Actinopterygii>FisheryInternal medicineMedicineMathematics

Abstract

fetched live from OpenAlex

The possible influence of parasites on the short-term and long-term growth and condition of yellow perch Perca flavescens was examined by investigating correlations between parasite abundance and specific growth variables. The following parasites were enumerated in age-1 yellow perch collected from Lake St. Pierre in June 2008: Apophallus brevis, Diplostomum spp., Ichthyocotylurus spp., Tylodelphys scheuringi, Phyllodistomum superbum, and Raphidascaris acus. Short-term growth was estimated using RNA/DNA ratios and long-term growth via the total length and condition as measured by the Fulton index. No correlation was found between parasite abundance and short-term growth, but a negative influence of combined infections of T. scheuringi and P. superbum on long-term growth was detected. In addition, the abundance of Ichthyocotylurus spp. was positively correlated with the condition of the yellow perch. Together these results suggest that limited or subtle pathogenic effects in juvenile fish are not discernable in recent growth but only in long-term growth indices. Furthermore, in future studies examination of parasite effects on fish growth should account for multiple infections.

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)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.022
GPT teacher head0.346
Teacher spread0.324 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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