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Record W1988208823 · doi:10.1139/f05-144

Growth potential and host mortality of the parasitic phase of the sea lamprey (<i>Petromyzon marinus</i>) in Lake Superior

2005· article· en· W1988208823 on OpenAlexvenueno aff
Jeffrey C. Jorgensen, James F. Kitchell

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersU.S. Fish and Wildlife Service
KeywordsPetromyzonLampreySalvelinusOncorhynchusTroutFisheryBiologyFish migrationBioenergeticsChinook windHost (biology)EcologyZoologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Landlocked Lake Superior sea lampreys (Petromyzon marinus) cause a significant but uncertain amount of mortality on host species. We used a sea lamprey bioenergetics model to examine the scope of host sizes vulnerable to death as a consequence of sea lamprey feeding and incorporated the bimodal lake-ward migration of parasitic sea lampreys. At their peak feeding rate and maximum size (P = 1.0, proportion of maximum consumption), spring migrants were capable of killing lean lake trout (Salvelinus namaycush) hosts ≤ 2.0 kg, which was larger than fall migrants (1.8 kg). Spring migrants feeding on Pacific salmon (coho (Oncorhynchus kisutch), Chinook (Oncorhynchus tshawytscha), and steelhead (Oncorhynchus mykiss)) killed hosts ≤ 2.0 kg, but fall migrants killed hosts as large as 2.8 kg. Although there is no direct empirical evidence, bioenergetics modeling suggests that it is plausible that some of the largest sea lampreys in Lake Superior spent more than one summer as parasites. Two-summer parasites readily attained sizes of sea-run adult anadromous sea lampreys and killed hosts from 3 to >5.5 kg in size. The maximum upper limit number of 2-kg hosts killed by two-summer parasites was nearly twice that of one-summer parasites.

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)0.000
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 score0.975
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.217
Teacher spread0.206 · 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

Explore more

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