MétaCan
Menu
Back to cohort
Record W2015485099 · doi:10.1080/08997659.2014.983278

The Impact of Egg Ozonation on Hatching Success, Larval Growth, and Survival of Atlantic Cod, Atlantic Salmon, and Rainbow Trout

2015· article· en· W2015485099 on OpenAlexaff
Jessica S. Fry, Juan Pérez Casanova, Dounia Hamoutene, L. Lush, Andy Walsh, C. Couturier

Bibliographic record

VenueJournal of Aquatic Animal Health · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsPetroleum Research Newfoundland and LabradorCollege of the North AtlanticMemorial University of Newfoundland
Fundersnot available
KeywordsBiologyHatchingRainbow troutLarvaFisheryAtlantic codZoologyFish <Actinopterygii>EcologyGadus

Abstract

fetched live from OpenAlex

The direct exposure of fish eggs to ozonated water has generated interest as a means of ensuring pathogen-free eggs without the use of harsh chemicals. However, there are numerous knowledge gaps, including safe contact times, exposure levels, and potential long-term effects on aquaculture species in both freshwater and seawater. The effect of different ozone (O3) doses (0.5-1.0, 1.5-2.0, and 2.5-3.0 mg of O3/L for 90 s) on recently fertilized eggs of Atlantic Cod Gadus morhua and eyed eggs of Atlantic Salmon Salmo salar and Rainbow Trout Oncorhynchus mykiss was evaluated in comparison with the effects of two commercial disinfectants: Perosan (0.004 mg/L) and Ovadine (100 mg/L). The impact of ozone application was evaluated based on hatching success, larval nucleic acid concentration, larval growth, and survival. Overall, results indicated that ozonation of Atlantic Cod eggs at a dose less than 3.0 mg/L for 90 s produced no negative effect on the larvae up to 30 d posthatch. Furthermore, ozonation of Atlantic Salmon and Rainbow Trout eggs generated no negative effect on the larvae, based on monitoring until 85% yolk sac re-absorption (16 d posthatch).

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)0.002
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 score0.003
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.023
GPT teacher head0.297
Teacher spread0.274 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Aquatic Animal HealthSame topicFish Ecology and Management StudiesFrench-language works237,207