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Record W4412072799 · doi:10.71161/ivb.144.1.2024.00015

The impact of hypoxia and heat stress on Corella inflata heart characteristics adds evidence to the functional role of heartbeat reversals

2025· article· en· W4412072799 on OpenAlexaff
Rebecca Krohman, Risa Ogushi, Jillian H. Stelfox, Catherine M. Ivy

Bibliographic record

VenueInvertebrate Biology · 2025
Typearticle
Languageen
FieldMedicine
TopicTraditional Chinese Medicine Analysis
Canadian institutionsWestern UniversityBamfield Marine Sciences Centre
Fundersnot available
KeywordsHeartbeatBiologyHypoxia (environmental)Heat stressNeuroscienceComputer scienceOxygen

Abstract

fetched live from OpenAlex

Marine habitats are experiencing changes in temperature and dissolved oxygen due to climate change, but how these changes are influencing the physiology of sessile invertebrates in the subtidal zone has not been well studied. Tunicates are a common subtidal invertebrate with a unique heart, in that their heartbeat can reverse directions. Tunicate heartbeat can be influenced by environmental stressors, but how combined low oxygen (hypoxia) and heat influence heart rate and heartbeat reversal is unknown. Corella inflata were collected and acclimated to lab conditions for 16-24 hours (∼13°C, ∼92% O2), then exposed to heat (∼18°C), hypoxic (∼31% O2), or heat and hypoxic (∼17°C and ∼31% O2) conditions for six hours. Heart rate and time between heartbeat reversals were measured after acclimation to lab conditions, exposure to a stressor, and recovery from the stressor. Heart rate increased with exposure to heat, hypoxia, and heat and hypoxia, with the greatest increase after exposure to both stressors. Time between heartbeat reversals increased with exposure to hypoxia and heat and hypoxia, but not heat. Our findings show that temperature and oxygen availability influence C. inflata heart rate and time between heartbeat reversals and suggests that tunicates may use heartbeat reversals to optimize oxygen and nutrient movement when exposed to stressors, which we propose as the Efficiency Hypothesis. Additionally, these findings provide insight into how tunicates may respond to changing ocean conditions in the future.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.276

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)0.0000.000

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 head0.029
GPT teacher head0.317
Teacher spread0.288 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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