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Record W2133323701 · doi:10.1577/t08-173.1

Temperature and Salinity Effects on Survival and Growth of Early Life Stage Shubenacadie River Striped Bass

2010· article· en· W2133323701 on OpenAlexaffabout
Adam Cook, J. Duston, Rod G. Bradford

Bibliographic record

VenueTransactions of the American Fisheries Society · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsNova Scotia Department of Agriculture
Fundersnot available
KeywordsSalinityJuvenileBass (fish)LarvaBiologyEstuaryAnimal scienceSerranidaeMorone saxatilisFisheryEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract A series of short, laboratory‐based trials was conducted on striped bass Morone saxatilis from the Shubenacadie River, Nova Scotia, Canada, starting with wild‐caught eggs and proceeding through to the early juvenile stage. The levels of the experimental factors—salinity (0–35‰) and temperature (10–30°C)—spanned the range occurring in the natal estuary. Survival of eggs to 1 d posthatch (dph) was highest, more than 60%, between 2‰ and 20‰ salinity and was reduced significantly (to <50%) only in salinities of 30‰ or greater. Similarly, survival of prefeeding larvae was reduced only at salinities above 30‰, suggesting that their salinity tolerance is higher than that of U.S. populations. Moreover, 1–7‐dph larvae were tolerant to temperature decreases that are lethal to other populations, with around 40% surviving between 10°C and 14°C at intermediate salinities. Older, 23‐dph larvae were less tolerant to cold, with fewer than 20% surviving 7 d at 10°C, but these larvae thrived at high temperature, exhibiting highest survival and growth at 26°C across salinities from 1‰ to 35‰. Growth of early juvenile stages (55–104 dph) was independent of salinity (1–30‰) and was highest between 26°C and 30°C, suggesting a temperature optimum similar to that of U.S. populations.

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 score0.944
Threshold uncertainty score0.112

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 head0.006
GPT teacher head0.202
Teacher spread0.195 · 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

Citations15
Published2010
Admission routes2
Has abstractyes

Explore more

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