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Transportation of juvenile tambaqui (Colossoma macropomum) in a closed system

2006· article· en· W2086668579 on OpenAlexfundno aff
Levy Carvalho Gomes, C. A. R. M. Araújo‐Lima, Adriana Regina Chippari-Gomes, Rodrigo Roubach

Bibliographic record

VenueBrazilian Journal of Biology · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsnot available
FundersUniversity of British ColumbiaConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsTambaquiBiologyDoseAnimal scienceBenzocaineJuvenileToxicologyFisheryFish <Actinopterygii>Ecology

Abstract

fetched live from OpenAlex

The objective of this study was to investigate the effect of density, duration and the use of additives to the water during the transportation of juvenile tambaqui (Colossoma macropomum) and use of this data to establish a safe transportation protocol for the species. The tested products and dosages were: salt (1000, 2000 and 3000 mg/L), gypsum (100, 300 and 500 mg/L) and benzocaine (10, 20 and 30 mg/L). Fish were transported in closed systems (plastic bag) at different densities and time periods of up to 24 h. Fish survival (FS) and water quality parameters were monitored immediately after transportation. The remaining fish were kept in floating cages in order to evaluate mortality which occurred up to 96 h after transportation (S96). The best fish density, additives dosages and time period of the transportation was estimated with a general linear model. The effect of the condition factor on FS and S96 was also evaluated. As expected, FS and S96 were significantly related to time and density. FS but not S96, were also were significantly related to treatment. FS with gypsum treatment was not different from controls and FS with table salt and benzocaine treatments were significantly reduced. The condition factor was not related to either FS or S96. FS was inversely correlated with carbon dioxide concentration. It was concluded that the additives did not improve fish transportation survival. Linear models were developed to predict the best transportation densities as a function of time.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.005
GPT teacher head0.216
Teacher spread0.212 · 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 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

Citations34
Published2006
Admission routes1
Has abstractyes

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