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Record W2150648826 · doi:10.1139/f06-017

Changes in seasonal energy dynamics of alewife (<i>Alosa pseudoharengus</i>) in Lake Michigan after invasion of dreissenid mussels

2006· article· en· W2150648826 on OpenAlexvenueno aff
Charles P. Madenjian, Steven A. Pot­hoven, John M. Dettmers, Jeffrey D. Holuszko

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsAlewifeBiologyFisheryOncorhynchusJuvenileEcologyZoologyAnimal scienceFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The dreissenid mussel invasion of Lake Michigan during the 1990s has been linked to a concomitant decrease in the abundance of the amphipod Diporeia. We tracked the seasonal energy dynamics of alewife (Alosa pseudoharengus) in Lake Michigan during 2002–2004 and compared our findings with previously published results for years 1979–1981. Adult alewife energy density exhibited a pronounced seasonal cycle during both the pre-invasion and post-invasion periods, with energy density in October or November nearly twice as high as that in early summer. However, on average, adult alewife energy density was 23% lower during the post-invasion period compared with the pre-invasion period. This significant decline in energy density was attributable to decreased importance of Diporeia in adult alewife diet. In contrast, energy density of juvenile alewives did not significantly differ between the pre-invasion and post-invasion periods. To attain a weight of 8 kg by age 4, bioenergetics modeling indicated that a Chinook salmon (Oncorhynchus tshawytscha) in Lake Michigan would have to consume 22.1% more alewives during the post-invasion period compared with the pre-invasion period.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.008
GPT teacher head0.185
Teacher spread0.177 · 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 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

Citations87
Published2006
Admission routes1
Has abstractyes

Explore more

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