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Record W4397021793 · doi:10.1080/17451000.2024.2342260

Temporal and spatial variability in metabolism of the Antarctic pelagic tunicate <i>Salpa thompsoni</i> Foxton, 1961

2024· article· en· W4397021793 on OpenAlexaff
Nataliya I. Minkina, Э. З. Самышев, Evgeny A. Pakhomov

Bibliographic record

VenueMarine Biology Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersRussian Academy of Sciences
KeywordsTunicatePelagic zoneBiologyCrustaceanEcologyZoology

Abstract

fetched live from OpenAlex

The mass-specific metabolic rates of the Antarctic pelagic tunicate Salpa thompsoni Foxton, 1961 were studied during March-April of 1998 and March 2002. The study revealed a large variation in metabolic rates and assessed sources of this variability. The main factors driving variability included density of tunicates in incubation containers (incubation density, e.g. the salp mass per unit volume of the respirometer), diel/circadian rhythms in salps, and spatial variability of their metabolic performance related to the feeding conditions. The mass specific respiration rates of both salp life forms (oozooids and blastozooids) appeared to be independent of their body mass. The salp-specific respiration rates at 3°C were strongly negatively influenced by their incubation density ranging between 2.0 and 90.4 gWW.l−1. Salp respiration rates adjusted to an incubation density of 3 gWW.l−1 in both oozooids and blastozooids followed similar circadian rhythms with the mean respiration rates of 79.5 and 41.5 μg O2 gWW−1 h−1, respectively. Deviation of these rates from actual field-measured respiration rates corrected for the salp density and diel variability during 1998 and 2002 identified effects of food concentrations, i.e. proxy of the plankton community development and composition, on the salp population performance.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.003
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 head0.031
GPT teacher head0.332
Teacher spread0.301 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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