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Record W2559244771 · doi:10.1098/rsos.160484

The role of cell replacement in benthic–pelagic coupling by suspension feeders

2016· article· en· W2559244771 on OpenAlexafffund
A Kahn, Sally P. Leys

Bibliographic record

VenueRoyal Society Open Science · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBenthic zonePelagic zonePopulationSuspension (topology)BiologyEcosystemCarbon fibersEcologyBiophysicsEnvironmental chemistryChemistryMaterials science

Abstract

fetched live from OpenAlex

Benthic-pelagic coupling through suspension feeders and their detrital pathways is integral to carbon transport in oceans. In food-poor ecosystems however, a novel mechanism of carbon recycling has been proposed that involves direct uptake of dissolved carbon by suspension feeders followed by shedding of cells as particulate carbon. We studied cell replacement rates in a range of cold-water sponge species to determine how universal this mechanism might be. We show that cell replacement rates of feeding epithelia in explants vary from 30 hours up to 7 days, and change during different seasons and life-history stages. We also found that feeding epithelia are not replaced through direct replication but instead arise from a population of stem cells that differentiate and integrate into epithelial tissues. Our results reveal a surprising amount of complexity in the control of cell processes in sponges, with cell turnover depending on environmental conditions and using stem cells as rate-limiting mechanisms. Our results also suggest that for species in cold water with high particulate organic matter, cell turnover is not the mechanism delivering carbon flux to surrounding communities.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0010.000
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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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

Citations37
Published2016
Admission routes2
Has abstractyes

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