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Record W6991929978

Initial effects of the exploitation of walleye, Stizostedion vitreum vitreum (Mitchill) on the boreal percid community of Henderson Lake, Northwestern Ontario / by Christopher P. Nunan. --

2017· other· en· W6991929978 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsStizostedionPredationPikePopulationPlanktivoreBorealPercidaeHydropsychidae
DOInot available

Abstract

fetched live from OpenAlex

The effect of large scale exploitation of walleye Stizostedion vitreum
\nvitreum on the boreal percid community of Henderson Lake, northwestern
\nOntario, was studied from 1979 to 1981. Investigations centered on the two
\nmajor predators in the community, the walleye and the northern pike Esox
\nlucius. Population estimates were done in 1979, 1980 and 1981, and the accuracy of Schnabel, Schumacher Eschmeyer and Peterson estimates were compared.
\nPrevious to exploitation (1979-1980) both walleye and northern pike exhibited the lowest production and P/?B ratios yet recorded for either species (walleye 4-14 yrs, P=1.01 kgha[superscript -1] yr[superscript -1], P/B =0.137; northern pike 7-14 yrs, P=0.716 kgha[superscript -1] yr[superscript -1] , P/?B =0.086). Low production in both species was partially attributed to competition for major prey species, and the small size
\nof available prey items. Sticklebacks Pungitius pungltius, yellow perch
\nPerca flavescens and mayfly subimagoes Ephemoptera sp. were the most important prey items in the lake. Long-term patterns of prey utilization by both predators showed considerable annual variation. Abundant white sucker and cyprinid species were not important in the diet of either walleye or northern pike, and may represent a net energy loss to the production of these two species.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0010.002
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 head0.028
GPT teacher head0.238
Teacher spread0.211 · 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.

Study designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

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