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Record W2173075406 · doi:10.1139/cjfas-2015-0009

The genetic legacy of more than a century of stocking trout: a case study in Rocky Mountain National Park, Colorado, USA

2015· article· en· W2173075406 on OpenAlexvenueno aff
Sierra M. Love Stowell, Christopher M. Kennedy, Stower C. Beals, Jessica L. Metcalf, Andrew Martin

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNational Park Service
KeywordsTroutStockingOncorhynchusEcologyBiologySubspeciesBiodiversityNational parkFisheryIntroduced speciesWildlife conservationWildlifeGeographyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Human introductions can obscure the diversity and distribution of native biota; hybridization with and replacement by introduced congeners is a primary conservation threat, particularly in salmonids. Cutthroat trout (Oncorhynchus clarkii) are an important component of biodiversity in the American West, and all recognized subspecies are targets for state and federal conservation efforts. Rocky Mountain National Park (RMNP) in northern Colorado is a microcosm of trout introductions that happened worldwide. We used a combination of extensive stocking records and molecular genetic data to ask whether native trout populations persist despite stocking and whether patterns in the distribution of cutthroat trout clades could be explained by source and intensity of stocking. Nearly 15 million cutthroat trout were stocked into RMNP from a mosaic of sources in the 20th century. A single lineage of cutthroat trout was historically native to each side of the Continental Divide in RMNP, but we detected at least five divergent clades of cutthroat trout in 34 localities on both sides of the Divide. The distribution of lineages was predicted by stocking pressure and source but not by which lineage was historically native. The future of mixed and non-native cutthroat trout populations in RMNP poses a substantial conservation challenge.

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 score0.466
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.030
GPT teacher head0.252
Teacher spread0.221 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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