MétaCan
Menu
Back to cohort
Record W2133076872 · doi:10.1139/f05-206

Have brook trout (<i>Salvelinus fontinalis</i>) displaced bull trout (<i>Salvelinus confluentus</i>) along longitudinal gradients in central Idaho streams?

2006· article· en· W2133076872 on OpenAlexvenueno aff
Bruce E. Rieman, James T. Peterson, Deborah L. Myers

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersU.S. Forest ServiceColorado State University
KeywordsTroutFontinalisSalvelinusSTREAMSFisheryEcologyBiologyHabitatOncorhynchusFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Invasions of non-native brook trout (Salvelinus fontinalis) have the potential for upstream displacement or elimination of bull trout (Salvelinus confluentus) and other native species already threatened by habitat loss. We summarized the distribution and number of bull trout in samples from 12 streams with and without brook trout in central Idaho and used hierarchical regression analysis to consider whether brook trout have displaced bull trout along gradients of temperature and elevation. Brook trout generally were observed in higher numbers downstream of bull trout. Brook trout presence, number, and both temperature and elevation were important variables explaining the observed distributions and number of bull trout among streams. Our analyses support the hypothesis that brook trout have displaced bull trout, but results were highly variable and stream dependent. Although brook trout appeared to have displaced bull trout to higher elevations or colder temperatures, there was no clear influence on overall number of bull trout. Brook trout probably do influence bull trout populations and facilitate if not cause local extinctions, but threats probably vary strongly with environmental conditions. Bull trout in smaller streams could be more vulnerable than those in larger streams.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.204
Teacher spread0.195 · 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

Citations127
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicFish Ecology and Management StudiesFrench-language works237,207