MétaCan
Menu
Back to cohort
Record W4385146184 · doi:10.1101/2023.07.21.547827

A temperature-controlled, circular maintenance system for studying growth and development of pelagic tunicates (Salps)

2023· preprint· en· W4385146184 on OpenAlexaff
Svenja J. Müller, Wiebke Weßels, Sara Driscoll, Evgeny A. Pakhomov, Lutz Auerswald, Katharina Michael, Bettina Meyer

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicMarine Invertebrate Physiology and Ecology
Canadian institutionsUniversity of British Columbia
FundersAlfred Wegener Institute Helmholtz Centre for Polar and Marine ResearchBundesministerium für Bildung und ForschungEuropean Commission
KeywordsPelagic zoneBiologyMediterranean seaEcologyBayOceanographyMediterranean climate

Abstract

fetched live from OpenAlex

Abstract Salps are pelagic tunicates that are able to form large blooms under favorable conditions by alternating between sexual and asexual reproduction. While their role in the regional carbon cycle is receiving attention, our knowledge of their physiology is still limited. This knowledge gap is mainly due to their fragile gelatinous nature, which makes it difficult to capture intact specimens and maintain them in the laboratory. We present here a modified kreisel tank system, that was tested onboard using the Southern Ocean salp Salpa thompsoni and station-based using the Mediterranean species Salpa fusiformis . Successful maintenance over days to weeks allowed us to obtain comparable relative growth and developmental rates as in situ , and provided insight into their potential life cycle strategies. By providing a starting point for successful maintenance, we hope to stimulate future experimental research on this understudied taxonomic group.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 science0.0010.001
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 head0.021
GPT teacher head0.199
Teacher spread0.179 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicMarine Invertebrate Physiology and EcologyFrench-language works237,207