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Factors Affecting Larval Sea Lamprey Growth and Length at Metamorphosis in Lampricide-Treated Streams

2001· article· en· W2005122623 on OpenAlexaff
Ronald W. Griffiths, F. W. H. Beamish, Bruce J. Morrison, Leslie Barker

Bibliographic record

VenueTransactions of the American Fisheries Society · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Guelph
FundersU.S. Department of the Interior
KeywordsMetamorphosisPetromyzonLarvaBiologySTREAMSAbiotic componentEcologyAnimal scienceZoology

Abstract

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Larval sea lampreys Petromyzon marinus in seven lampricide‐treated streams were studied to assess the effects of density and abiotic factors on growth, length at metamorphosis, and age at metamorphosis. Support for density‐dependent growth was not found in these streams. A linear relationship between total length and age was found for all populations. The daily growth of larvae in lampricide‐treated streams was similar to that of populations that were never exposed to lampricide. Furthermore, the growth of stocked residual populations did not increase following a lampricide‐induced reduction in larval density. Differences in growth and length at metamorphosis among these streams were accounted for by abiotic factors. Larval growth was highest in streams with an annual water temperature around 8°C, moderate discharge (0.5–2.0 m3/s), and high conductivity (>300μS). Length at metamorphosis, on the other hand, was inversely related to conductivity, annual discharge, and annual mean temperature. A model of age at metamorphosis based on larval growth and length at metamorphosis, both as functions of water temperature, showed that age at metamorphosis was lower for populations showing linear growth with age (typically low‐density populations) than for those showing compensatory growth with age (typically high‐density populations).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

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)0.0000.000

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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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

Citations27
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the American Fisheries SocietySame topicFish Ecology and Management StudiesFrench-language works237,207