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Record W3024603989 · doi:10.1038/s41598-020-65220-9

Warming and acidification threaten glass sponge Aphrocallistes vastus pumping and reef formation

2020· article· en· W3024603989 on OpenAlexafffund
Angela Stevenson, Stephanie K. Archer, Jessica Schultz, Anya Dunham, Jeff Marliave, Patrick T. Martone, Christopher D. G. Harley

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersNatural Sciences and Engineering Research Council of CanadaMarine Environmental Observation Prediction and Response Network
KeywordsSpongeReefOcean acidificationOceanographyGreat barrier reefEnvironmental scienceFisheryClimate changeGeologyBiologyPaleontology

Abstract

fetched live from OpenAlex

The glass sponge Aphrocallistes vastus contributes to the formation of large reefs unique to the Northeast Pacific Ocean. These habitats have tremendous filtration capacity that facilitates flow of carbon between trophic levels. Their sensitivity and resilience to climate change, and thus persistence in the Anthropocene, is unknown. Here we show that ocean acidification and warming, alone and in combination have significant adverse effects on pumping capacity, contribute to irreversible tissue withdrawal, and weaken skeletal strength and stiffness of A. vastus. Within one month sponges exposed to warming (including combined treatment) ceased pumping (50-60%) and exhibited tissue withdrawal (10-25%). Thermal and acidification stress significantly reduced skeletal stiffness, and warming weakened it, potentially curtailing reef formation. Environmental data suggests conditions causing irreversible damage are possible in the field at +0.5 °C above current conditions, indicating that ongoing climate change is a serious and immediate threat to A. vastus, reef dependent communities, and potentially other glass sponges.

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 score0.003
Threshold uncertainty score0.007

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 head0.018
GPT teacher head0.234
Teacher spread0.216 · 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

Citations30
Published2020
Admission routes2
Has abstractyes

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