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Record W2554363235 · doi:10.4172/2155-9546.1000451

Evaluation of Three External Marking Methods of Farmed Atlantic Salmon for the Future Use of Differentiating it From Wild Atlantic Salmon

2016· article· en· W2554363235 on OpenAlex
Atle Mortensen, Øyvind J. Hansen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Aquaculture Research & Development · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsFisheryBiologyAquacultureFish <Actinopterygii>

Abstract

fetched live from OpenAlex

We evaluated different external marking methods for farmed salmon to differentiate it from wild salmon without any special tools. Three marking methods were tested: 1) Adipose fin (AF) removal, 2) Freeze branding (FB) and, 3) Visible Implant Elastomer (VIE). Location of the marking method on the fish, combination of marking methods and degree of AF removal were tested in three experiments. Atlantic salmon parr weighing 20 g were marked either with individual marks or in combination of two. Further all the fish were also PIT tagged. They were kept in freshwater tanks for 4 months and later after smoltification, smolts were transferred to sea cages and kept for another 4 months. At the end of four (freshwater phase) and ten (sea cages) months, growth, survival and mark retention were recorded. All these methods had no significant effects on growth and survival compared to the control (no mark but only PIT tagged). Our results showed that of these methods, only complete removal of the adipose fin met the requirements for mark retention and was the cheapest and easiest method to automate. However, a larger commercial scale long-term testing of the AF clipping is required prior to implementing it. Further development of an automated fin clipping in combination with vaccination and an open discussion with consumers, buyers, and environmental groups are also warranted.

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.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
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)0.0000.000

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 head0.112
GPT teacher head0.378
Teacher spread0.267 · 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