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The status of Arctic charr <i>Salvelinus alpinus</i> in Britain and Ireland

2006· article· en· W2090575414 on OpenAlexaboutno aff
Peter S. Maitland, Ian J. Winfield, Ian McCarthy, Fran Igoe

Bibliographic record

VenueEcology Of Freshwater Fish · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersJohns Hopkins University
KeywordsSalvelinusArcticEcologyArctic charGeographyExtinction (optical mineralogy)PopulationFisheryRange (aeronautics)BiologyFish <Actinopterygii>Trout

Abstract

fetched live from OpenAlex

Abstract – The Arctic charr occurs in lakes across Britain and Ireland and was previously described here as 15 separate species. Most authorities now agree that all these stocks belong to a single polymorphic species complex Salvelinus alpinus (L.). This fish is given little protection in British and Irish law and there has been a steady loss of natural populations in recent years in all the countries concerned. A few new stocks have been created either intentionally or accidentally. In Scotland, only a small proportion of the 258 recorded natural populations has been studied and at least 12 of these are now extinct. There are at least four introduced populations originating from native Scottish stocks, but the fate of stocks introduced from Canada for aquaculture is uncertain. In England, there are eight extant populations in Cumbria and four others extinct. The status of introduced stocks in England is uncertain but there is probably one population surviving in Yorkshire. In Wales, eight lakes with resident Arctic charr populations have been recorded, three of these populations are natural, one is extinct and four have been introduced. In Ireland, of the 74 known populations, approximately 30% are extinct. There is no evidence to indicate that introduced stocks (some of them from Iceland) in a small number of lakes have survived there. A range of factors is involved in the extinction of populations and these include pollution, eutrophication, acidification, afforestation, engineering, exploitation, aquaculture, introductions and climate change. Much research remains to be done and unique stocks of this valuable species will continue to be lost unless positive action is taken through local conservation management backed by appropriate national legislation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations52
Published2006
Admission routes1
Has abstractyes

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