MétaCan
Menu
Back to cohort
Record W2080055854 · doi:10.1139/f04-083

Over-winter lipid depletion and mortality of age-0 rainbow trout (<i>Oncorhynchus</i><i>mykiss</i>)

2004· article· en· W2080055854 on OpenAlexvenueno aff
Peter A. Biro, Ashley E Morton, John R. Post, Eric A. Parkinson

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRainbow troutTroutHatcheryBiologyAnimal scienceStarvationSalmonidaeEcologyFish <Actinopterygii>FisheryZoologyEndocrinology

Abstract

fetched live from OpenAlex

In this study we identify the size-dependent risk of winter starvation mortality as a strong selective pressure on age-0 rainbow trout (Oncorhynchus mykiss) that could promote the risk-taking behaviour and allocation of energy to lipids previously observed in young trout cohorts. Age-0 trout subjected to simulated winter starvation conditions gradually depleted lipid reserves to a critical minimum lipid content below which death occurred. Small fish with lower lipid content exhausted lipid reserves earlier, and experienced high mortality rates sooner, than larger fish with greater lipid content. Consequently, winter starvation endurance was dependent upon size-dependent lipid reserves and winter duration. To validate the laboratory findings in the field, we stocked several size classes of hatchery-raised trout with known lipid content at the start of winter into two experimental lakes, and estimated survival and lipid depletion at winter's end. Larger age-0 trout had greater initial lipid reserves than smaller trout. Individuals depleted most of their lipid reserves over the winter, and experienced mortality that ranged from just under 60% for the largest individuals to just over 90% of the smallest individuals. Many survivors had lipid contents near, but none were below, the minimum lipid content determined in the laboratory.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.972

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 studies0.0000.002
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 head0.015
GPT teacher head0.221
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 teacher head, 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

Citations239
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicFish Ecology and Management StudiesFrench-language works237,207