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Record W2069467707 · doi:10.1071/mf12316

Osmoregulation and survival of two mysid species of Tenagomysis in southern estuaries of New Zealand

2013· article· en· W2069467707 on OpenAlexaff
Sourav Paul, Martin Krkošek, P. Keith Probert, Gerard P. Closs

Bibliographic record

VenueMarine and Freshwater Research · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEstuarySalinityBiologyOsmoregulationEcologyBrackish waterFishery

Abstract

fetched live from OpenAlex

The mysid shrimps Tenagomysis chiltoni and T. novaezealandiae are abundant in southern New Zealand estuaries; however, little is known of their osmoregulatory capacity and survival. We investigated their osmoregulation and survival under salinities of 0, 5, 10, 15, 20, 25, 30 and 33 at 5°C and 20°C, to evaluate if the variation in salinity limits their distribution in estuaries. T. chiltoni and T. novaezealandiae maintained species-specific haemolymph concentrations across the salinities tested. According to AIC model selection statistics, for osmoregulatory capacity, the combined effects of salinity and temperature emerged as the most parsimonious. For survival, the non-linear effect of salinity was found as the most supported model given the data. Mortality of T. chiltoni and T. novaezealandiae increased towards the extremes of fresh and salt water but was lower in intermediate salinities (10–25). The ability of these species to osmoregulate and survive were limited at 5°C, but improved at 20°C. Life-history stage was found to be critical for explaining the variations in survival. We concluded that salinity could influence osmoregulation and survival of Tenagomysis spp., and when interacting with temperature and life-history stage, may partly explain why both shrimp species could be found in intermediate salinities and why T. chiltoni is more prevalent in the upper reaches of southern New Zealand estuaries.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.037
GPT teacher head0.280
Teacher spread0.244 · 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 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

Citations12
Published2013
Admission routes1
Has abstractyes

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