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Record W2398520084 · doi:10.1002/ecy.1438

Sea‐louse parasites on juvenile wild salmon in the <scp>B</scp>roughton <scp>A</scp>rchipelago, <scp>B</scp>ritish <scp>C</scp>olumbia, <scp>C</scp>anada

2016· article· en· W2398520084 on OpenAlexaffabout
Stephanie J. Peacock, Andrew W. Bateman, Martin Krkošek, Brendan Connors, Scott D. Rogers, Lauren Portner, Zephyr Polk, C.N.Bollich and B.D.Webb, Alexandra Morton

Bibliographic record

VenueEcology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsRaincoast Conservation FoundationUniversity of TorontoSimon Fraser UniversityVancouver Coastal HealthUniversity of Alberta
Fundersnot available
KeywordsLepeophtheirusOncorhynchusLouseBiologyFisheryJuvenileAquacultureFish <Actinopterygii>EcologyZoology

Abstract

fetched live from OpenAlex

The global expansion of aquaculture has changed the structure of fish populations in coastal environments, with implications for disease dynamics. In Pacific Canada, farmed salmon act as reservoir hosts for parasites and pathogens, including sea lice (Lepeophtheirus salmonis and Caligus clemensi) that can transmit to migrating wild salmon. Assessing the impact of salmon farms on wild salmon requires regular monitoring of sea-louse infections on both farmed and wild fish. Since 2001, we have collected juvenile pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon annually at three sites in the Broughton Archipelago in British Columbia, Canada, during the annual juvenile salmon migration from fresh water to the open ocean. From sampled fish, we recorded counts of parasitic copepodid-, chalimus-, and motile-stage sea lice. We report louse abundances as well as supplementary observations of fish size, development, and health.

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 score0.757
Threshold uncertainty score0.483

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 studies0.0010.001
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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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