MétaCan
Menu
Back to cohort
Record W2544130301 · doi:10.15273/pnsis.v47i1.3379

GROWTH AND OVERPOPULATION OF YELLOW PERCH AND THE APPARENT EFFECT OF INCREASED COMPETITION ON BROOK TROUT IN LONG LAKE, HALIFAX COUNTY, NOVA SCOTIA

2012· article· en· W2544130301 on OpenAlexaffvenueabout
Cathy L. Munro

Bibliographic record

VenueProceedings of the Nova Scotian Institute of Science · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsNova Scotia Department of Agriculture
Fundersnot available
KeywordsPerchNova scotiaTroutFisheryCompetition (biology)BiologyPopulationAnimal scienceEcologyFish <Actinopterygii>GeographyDemography

Abstract

fetched live from OpenAlex

A fish survey was conducted on Long Lake, Woodens River, Halifax County, Nova Scotia during May 2005. A total of 2711 yellow perch were captured over a twelve day period and were the most abundant fish. Fifty-eight yellow perch were sampled for length, weight, scales, and sex. Total length of yellow perch ranged from 81mm to 276 mm with a mean of 133mm. Ages determined from scale analysis ranged from 2 to 13 years but 95% were younger than 8 years of age. Age at maturity was 2 years. The Von Bertalanffy growth relationship for yellow perch described slow growth and suggested stunting which is consistent in crowded populations. Increased abundance of yellow perch and reduced abundance of brook trout has been reported by anglers in the Woodens River system and was evident from our catches. The apparent effect of increased, intraguild competition on the brook trout population is discussed.Keywords: yellow perch, brook trout, overpopulation, stunting, intraguild competition.

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 score0.240
Threshold uncertainty score0.483

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 studies0.0010.001
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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

Citations2
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueProceedings of the Nova Scotian Institute of ScienceSame topicFish Ecology and Management StudiesFrench-language works237,207