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Record W2096813363 · doi:10.1139/f03-107

Thermal heterogeneity, stream channel morphology, and salmonid abundance in northeastern Oregon streams

2003· article· en· W2096813363 on OpenAlexvenueno aff
Joseph L. Ebersole, William J. Liss, Christopher A. Frissell

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOncorhynchusChinook windRainbow troutRiparian zoneHabitatSTREAMSAbundance (ecology)TroutEnvironmental scienceEcologyFisherySalmonidaeRelative species abundanceCobbleBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Heterogeneity in stream water temperatures created by local influx of cooler subsurface waters into geomorphically complex stream channels was associated with increased abundance of rainbow trout (Oncorhynchus mykiss) and chinook salmon (Oncorhynchus tshawytscha) in northeastern Oregon. The addition of cold water patch frequency and area as explanatory variables in salmonid habitat models indicated that doubling of cold water patch frequency was associated with increases in rainbow trout and chinook salmon abundances of 31% and 59%, respectively. Doubling of cold water patch area was associated with changes of 10% in rainbow trout abundance but was not associated with chinook abundance after accounting for other habitat factors. The physiognomy, distribution, and connectivity of cold water patches, important attributes determining the effectiveness of these habitats as thermal refuges for stream fishes, were associated with channel bedform and riparian features. Monitoring of thermal heterogeneity and salmonid populations in response to ongoing habitat restoration efforts will provide additional insights into causal relationships among these factors.

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 score0.365
Threshold uncertainty score0.818

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 studies0.0000.001
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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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

Citations167
Published2003
Admission routes1
Has abstractyes

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