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Record W4210916181 · doi:10.1002/zoo.21684

(Very) long‐term transport of <i>Silurus glanis</i>, <i>Carcharhinus melanopterus</i>, <i>Scomber colias</i>, <i>Trachurus picturatus, Polyprion americanus</i>, <i>Rhinoptera marmoratus</i>, <i>Salmo salar</i>, <i>Scomber scombrus</i>, <i>Sardina pilchardus</i>, and others, by land, water and air

2022· article· en· W4210916181 on OpenAlexaff
João P.S. Correia, Gheylen Daghfous, David Silva, Gonçalo Graça, Ivan Beltran, João Reis, José P. Marques, Luís Silva, Rui Guedes, Telmo Morato

Bibliographic record

VenueZoo Biology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBiologySalmoScomberFisherySodium bicarbonateCockleFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract In this paper, we cover 4 years of live fish transports that ranged from 14 to 200 h (8 days), and bioloads from 3.8 to 76.9 kg/m 3 . The key ingredients for success in all trips, where virtually no mortality occurred, was atributed to (1) pre‐buffering the water with sodium bicarbonate and sodium carbonate at 50 g/m 3 (each)—and/or ATM Alka‐Haul TM at 25 g/m 3 —and applying additional (partial or full) doses throughout each transport, whenever the tanks were accessible; (2) pre‐quenching ammonia with ATM Triage TM at 32 g/m 3 , and applying additional (partial or full) doses throughout each transport, whenever the tanks were accessible; (3) keeping the dissolved oxygen saturation rate above 100%, ideally above 150%; (4) Keeping temperature on the lower limit of each species' tolerance range; (5) Using foam fractionators to effectively eliminate organic matter from the water and (6) Using pure sine wave inverters, which allows for a steady supply of electrical current throughout the transport. The use of a ‘preventive’ versus ‘corrective’ pH buffering philosophy is also discussed.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.197
Teacher spread0.193 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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