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Record W3199030377 · doi:10.1111/jfd.13535

Quantifying key parameters related to the life cycle of <i>Caligus rogercresseyi</i>

2021· article· en· W3199030377 on OpenAlexaff
Jaewoon Jeong, Gregor McEwan, Gabriel Arriagada, Cristian Gallardo‐Escárate, Crawford W. Revie

Bibliographic record

VenueJournal of Fish Diseases · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsHealth PEIUniversity of Prince Edward Island
FundersFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasAgencia Nacional de Investigación y DesarrolloUniversidad de Concepción
KeywordsBiologyLepeophtheirusAquacultureFisheryEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The salmon louse Caligus rogercresseyi (Boxshall and Bravo 2000) is a common ectoparasite of farmed salmonids in Chile. Sea lice can negatively impact the growth of hosts, adversely affecting aquaculture productivity. Unlike Lepeophtheirus salmonis (Krøyer, 1838), whose life cycle parameters have been well studied due to its importance in the Northern Hemisphere, for C. rogercresseyi no single source exists that quantifies the parameters required to model this ectoparasite's life cycle. Given that different species of sea lice have substantially different biological characteristics, it is important to parameterize the life cycle of C. rogercresseyi using appropriate observational data, rather than simply trying to adapt parameters developed for L. salmonis. Using data from existing literature, we quantified the development and survival rates for each stage in the C. rogercresseyi life cycle. We illustrate how development rates are affected by water temperature and explore the important impacts of salinity on rates of survival. We present equations that can be used to model development periods and survival proportions given certain water temperature and salinity profiles. While key parameters to quantitatively model the life cycle of C. rogercresseyi are presented, further research is required to adequately model the complete population dynamics of this ectoparasite on Chilean salmon farms and consequently to support decision-making to achieve effective control and mitigation.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.023
GPT teacher head0.323
Teacher spread0.300 · 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.

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

Citations7
Published2021
Admission routes1
Has abstractyes

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