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Record W2562472729 · doi:10.1242/jeb.146076

The energetic cost of filtration by demosponges and their behavioural response to ambient currents

2016· article· en· W2562472729 on OpenAlexafffund
Danielle A. Ludeman, Matthew A. Reidenbach, Sally P. Leys

Bibliographic record

VenueJournal of Experimental Biology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaIran National Science FoundationCompany of Biologists
KeywordsFiltration (mathematics)PhysicsEnvironmental scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

Sponges (Porifera) are abundant in most marine and freshwater ecosystems, and as suspension feeders they play a crucial role in filtering the water column. Their active pumping enables them to filter up to 900 times their body volume of water per hour, recycling nutrients and coupling a pelagic food supply with benthic communities. Despite the ecological importance of sponge filter feeding, little is known about how sponges control the water flow through their canal system or how much energy it costs to filter the water. Sponges have long been considered textbook examples of animals that use current-induced flow. We provide evidence that suggests that some species of demosponge do not use current-induced flow; rather, they respond behaviourally to increased ambient currents by reducing the volume of water filtered. Using a morphometric model of the canal system, we also show that filter feeding may be more energetically costly than previously thought. Measurements of volumetric flow rates and oxygen removal in five species of demosponge show that pumping rates are variable within and between species, with the more oxygen consumed the greater the volume filtered. Together, these data suggest that sponges have active control over the volume of water they process, which may be an adaptation to reduce the energetic cost of filtration in times of high stress.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.025
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.284
Teacher spread0.272 · 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 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

Citations53
Published2016
Admission routes2
Has abstractyes

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