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Record W2050516896 · doi:10.1111/are.12364

Hot water immersion lowers survival, shell growth rate and lysosomal membrane stability of oysters<i>Crassostrea virginica</i>(Gmelin)

2013· article· en· W2050516896 on OpenAlexafffund
Élise Mayrand, Tina Sonier, Luc A. Comeau

Bibliographic record

VenueAquaculture Research · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsFisheries and Oceans CanadaUniversité de Moncton
FundersFisheries and Oceans Canada
KeywordsOysterCrassostreaBiologyImmersion (mathematics)Animal scienceFisheryFoulingMembraneBiochemistry

Abstract

fetched live from OpenAlex

This study compares the effect of two anti-fouling treatments, hot water immersion (15 s at 60°C) and air drying (72 h) on the physiological status of the Eastern oyster Crassostrea virginica. The negative impact of hot water immersion was greater than that of air drying, but varied depending on the initial size of the oysters (40 vs. 60 mm shell height) and the time of the year (June vs. August). Groups treated with hot water exhibited a higher proportion of haemocytes with destabilized lysosomal membranes (HDLM; 47.5 ± 3.1%) than those exposed to air drying (37.5 ± 2.9%). This suggests that the oyster immunocompetency may be lowered by hot water immersion. Overall, the large oysters had lower HDLM values (32.9 ± 3.5%) than the small individuals in June (45.7 ± 2.8%) but similar values in August (46.6 ± 3.5%). Small oysters subjected to hot water immersion in June exhibited a 50% reduction in shell growth and a 50% mortality rate after one month. Our results indicate that air drying is more suitable than hot water immersion as an anti-fouling treatment for <45 mm oysters.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.032
GPT teacher head0.290
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations3
Published2013
Admission routes2
Has abstractyes

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