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Record W2810026317 · doi:10.1111/jfb.13684

Oust the louse: leaping behaviour removes sea lice from wild juvenile sockeye salmon <scp><i>Oncorhynchus nerka</i></scp>

2018· article· en· W2810026317 on OpenAlexafffund
Emma M. Atkinson, Andrew W. Bateman, Lawrence M. Dill, Martin Krkošek, John D. Reynolds, Sean C. Godwin

Bibliographic record

VenueJournal of Fish Biology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of TorontoUniversity of VictoriaVancouver Coastal HealthSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaPacific Salmon FoundationSimon Fraser UniversityUniversity of Toronto
KeywordsOncorhynchusLepeophtheirusBiologyJuvenileFisheryZoologyJuvenile fishFish <Actinopterygii>EcologyAquaculture

Abstract

fetched live from OpenAlex

We conducted a manipulative field experiment to determine whether the leaping behaviour of wild juvenile sockeye salmon Oncorhynchus nerka dislodges ectoparasitic sea lice Caligus clemensi and Lepeophtheirus salmonis by comparing sea-lice abundances between O. nerka juveniles prevented from leaping and juveniles allowed to leap at a natural frequency. Juvenile O. nerka allowed to leap had consistently fewer sea lice after the experiment than fish that were prevented from leaping. Combined with past research, these results imply potential costs due to parasitism and indicate that the leaping behaviour of juvenile O. nerka does, in fact, dislodge sea lice.

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 score0.006
Threshold uncertainty score0.012

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)0.0020.000

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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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