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Record W6990868622

Epibenthic megafauna associated with sponge grounds formed by the unique glass sponge Vazella pourtalesii in Emerald Basin, Nova Scotia, Canada

2018· dissertation· en· W6990868622 on OpenAlexaboutno aff

Bibliographic record

VenueBergen Open Research Archive (BORA) (University of Bergen) · 2018
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsnot available
Fundersnot available
KeywordsMegafaunaBiotaSpongeHabitatFishingEcosystem
DOInot available

Abstract

fetched live from OpenAlex

Large, dense aggregations of sponges or “sponge grounds” have seen a surge of scientific interest in recent years. The pivotal ecological functions of sponges may warrant conservation measures that have been neglected in the past. The slow growth and low recovery potential of some deep-sea sponges, combined with their fragile morphologies, contributes to vulnerability to mobile fishing gear, particularly bottom trawling. The largest monospecific aggregation of Vazella pourtalesii, the Russian hat, was recently described off the Scotian Shelf between 75-275 m depth, extending over 8,500 km2 . Here I describe and compare the epibenthic megafauna inside and outside sponge grounds, and, if the condition (live, dead and damaged) of Vazella pourtalesii has an effect on the local biota and its composition. Building on previous work, I also account for the effect of substrate to see if Vazella pourtalesii enhances local biota, as previous work has shown. The results suggested that Vazella pourtalesii had a positive influence on local epibenthic megafauna, as well as the community compositions; however, more data is needed to provide a complete answer. This research will aid managers in the future, by helping to untangle the intricacies of this interesting habitat so as to avoid further significant adverse impacts.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.280
Teacher spread0.258 · 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.

Study designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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