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Record W2007504242 · doi:10.1080/15222055.2012.711275

Discriminating Rainbow Trout Sources Using Freshwater and Marine Otolith Growth Chemistry

2012· article· en· W2007504242 on OpenAlexafffundabout
Geoff Veinott, Rex Porter

Bibliographic record

VenueNorth American Journal of Aquaculture · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans Canada
FundersGovernment of Canada
KeywordsRainbow troutOtolithBiologyFisheryZoologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract Rainbow Trout Oncorhynchus mykiss are nonindigenous to Newfoundland. Subsequent to the development of marine cage rearing of Rainbow Trout in the Atlantic provinces in the early 1970s, Rainbow Trout have been captured in 33 rivers on the west and south coast of Newfoundland. These escapees may have negative impacts on wild populations, particularly Atlantic Salmon Salmo salar and Brook Trout Salvelinus fontinalis. In this study, the chemical fingerprints in the freshwater and marine growth sections of otoliths were used to distinguish three groups of Rainbow Trout of known origins: two hatcheries and one wild population. The results were then used to assign fish of unknown origin to the three known-origin groups and thus estimate the proportion of escapees. The three known sources produced distinct chemical fingerprints in the freshwater growth of the otoliths (cross validation test, average accuracy of over 93%); whereas, the marine growth in the otoliths produced a single chemical fingerprint for the two hatchery-origin groups distinct from the wild population. Results indicated that at least 60% of the unknown-origin fish were aquaculture escapees. Vaterite was encountered in 70–80% of the known hatchery-origin fish, 0% in the wild population, and 50% in the escapees. It appears that escapees with vaterite had a lower survival rate. The presence–absence of vaterite did not appear to be useful in distinguishing escapees from a wild population.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.420

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)0.0000.000

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 head0.007
GPT teacher head0.211
Teacher spread0.203 · 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 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

Citations4
Published2012
Admission routes3
Has abstractyes

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