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Record W2153322449

Recovery and decline of lake whitefish in U.S. waters of eastern Lake Ontario, 1980-2001

2005· article· en· W2153322449 on OpenAlexaboutno aff
Randall W. Owens, Robert O’Gorman, Thomas H. Eckert, Brian F. Lantry, Dawn E. Dittman

Bibliographic record

VenueLincoln (University of Nebraska) · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersU.S. Geological Survey
KeywordsGeographyArchaeologyGeologyOceanographyEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

The lake whitefish (Coregonus clupeaformis) was an important member of the native fish community and a valued commercial species in Lake Ontario. Lake whitefish were common in U.S. waters of the lake until 1965 and very abundant in Canadian waters through the early 1970s, although their numbers declined shortly thereafter. During 1975-1985, lake whitefish stocks remained depressed throughout the lake as a result of the combined effects of degraded water quality, overfishing, and predation. Rainbow smelt (Osmerus mordax) probably preyed on whitefish fry, and sea lamprey (Petromyzon marinus) preyed on adults. During 1985-1987, lake whitefish stocks began to recover in eastern Lake Ontario, and their buildup continued into the mid-1990s. Reasons for the recovery likely included control of the sea lamprey population and a reduction in the number of piscivorous rainbow smelt. By 1997, lake whitefish abundance had declined severely again; some fish appeared to have dispersed from the northeastern to the southeastern regions of the lake, and the depth of capture increased. We believe that the collapse of Diporeia spp. populations during 1992-1999 was responsible for the decline in the lake whitefish populations and the shifts in geographic and bathymetric distribution because lake whitefish fed primarily on Diporeia spp. After the collapse of Diporeia spp. populations, lake whitefish in southeastern Lake Ontario fed on Mysis relicta and quagga mussels (Dreissena bugensis). Changing from a diet of high-lipid Diporeia spp. to low-lipid dreissenids and foraging on Mysis relicta at lower temperatures are apparently hampering the rebuilding of lake whitefish stocks.

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 score0.961
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.172
Teacher spread0.164 · 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

Citations10
Published2005
Admission routes1
Has abstractyes

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