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Record W4281783040 · doi:10.1101/2022.06.02.494586

Heat stress does not induce wasting symptoms in the giant California sea cucumber ( <i>Apostichopus californicus</i> )

2022· preprint· en· W4281783040 on OpenAlexaffabout
Declan Dawson Taylor, Jonathan James Farr, Em G Lim, Jenna Laurel Fleet, Sara J. Smith, Daniel M. Wuitchik

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicEchinoderm biology and ecology
Canadian institutionsUniversity of WinnipegSimon Fraser UniversityUniversity of AlbertaBamfield Marine Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsApostichopus japonicusSea cucumberWastingBayHeat stressBiologyMass wastingEcologyFisheryMedicineOceanographyAnimal scienceEndocrinologySediment

Abstract

fetched live from OpenAlex

Abstract Oceanic heat waves have significant impacts on disease dynamics in marine ecosystems. A severe sea cucumber wasting event occurred in Nanoose Bay, British Columbia, Canada, following an extreme heat wave, resulting in mass mortality of Apostichopus californicus . Here, we sought to determine if heat stress in isolation could trigger wasting symptoms in A. californicus . We exposed sea cucumbers to i) a simulated marine heat wave (22ºC), ii) an elevated temperature treatment (17ºC), or iii) control conditions (12ºC). We measured the presence of skin ulcers, mortality, posture maintenance, antipredator defences, spawning, and organ evisceration during the 79-hour thermal exposure, as well as 7-days post-exposure. Both the 22°C and 17°C treatments elicited stress responses where individuals exhibited a reduced ability to maintain posture and an increase in stress spawning. The 22ºC heat wave was particularly stressful, as it was the only treatment where mortality was observed. However, none of the treatments induced wasting symptoms as observed in the Nanoose Bay event. This study provides evidence that sea cucumber wasting is not triggered by heat stress in isolation, leaving the cause of the mass mortality event observed in Nanoose unknown.

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)0.0010.000

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 head0.013
GPT teacher head0.207
Teacher spread0.194 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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