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Record W3080914754 · doi:10.1111/faf.12496

A meta‐analysis of gas bubble trauma in fish

2020· article· en· W3080914754 on OpenAlexafffund
Naomi K. Pleizier, Dirk A. Algera, Steven J. Cooke, Colin J. Brauner

Bibliographic record

VenueFish and Fisheries · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsCarleton UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSupersaturationFish <Actinopterygii>Freshwater fishMeta-analysisGillFisheryBiologyEnvironmental scienceEcologyChemistryMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Total dissolved gas (TDG) supersaturation generated by dams is known to cause gas bubble trauma (GBT) and mortality in fish, but despite many studies on the topic, there have been no recent attempts to systematically review the data. We conducted a systematic review and meta‐analysis to determine how different levels of TDG supersaturation in laboratory experiments impact mortality and GBT outcomes of freshwater fishes. We also examined all TDG laboratory studies on freshwater fish to identify research gaps in the GBT literature. Factors that improved the linear mixed‐effects models and Cox proportional hazards models of the relationship between TDG supersaturation and time to 50% mortality, time to 10% mortality, time to the appearance of bubbles in the gills and time to external GBT symptoms include depth, temperature, oxygen‐to‐nitrogen ratios, species, body mass, the interaction between TDG and depth and author group for one or more of the models of the relationship between TDG and GBT outcomes. Of the 99 GBT studies we found in our search, 74% quantified mortality outcomes, with limited assessment of quantitative behavioural, histological and performance outcomes. Moreover, the majority of studies were conducted on salmonids. We therefore recommend additional studies on non‐salmonid species to enhance our understanding of the mechanisms of GBT and community effects with use of more diverse sublethal outcomes. We also recommend random subject allocation to treatments, complete reporting, consistent methods between treatments and the use of control groups (which were often lacking) for more rigorous experimental designs.

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)0.000
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 score0.114
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

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)0.0050.000

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 head0.040
GPT teacher head0.215
Teacher spread0.175 · 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

Citations65
Published2020
Admission routes2
Has abstractyes

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