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Record W2158891656 · doi:10.1139/f01-133

Estimating in-river survival of migrating salmonid smolts using radiotelemetry

2001· article· en· W2158891656 on OpenAlexvenueno aff
John R. Skalski, James Lady, Richard L. Townsend, Albert E. Giorgi, John R. Stevenson, Charles M. Peven, Robert D. McDonald

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransponder (aeronautics)Environmental scienceRainbow troutFisheryMark and recaptureTelemetryMaximum likelihoodHydrology (agriculture)OncorhynchusFish <Actinopterygii>StatisticsBiologyGeographyMeteorologyGeologyEngineeringTelecommunicationsGeotechnical engineering

Abstract

fetched live from OpenAlex

A field study to estimate the survival of outmigrating steelhead (Oncorhynchus mykiss) smolts using radiotelemetry methods is illustrated. A paired release–recapture design was used to estimate pool (i.e., reservoir), dam, and project (i.e., reservoir plus dam) survival at two mid-Columbia River hydroprojects based on maximum likelihood estimation. The release and detection scheme was designed to minimize the possibility of detecting false-positive radio signals from smolts that might have died upstream during the hydroproject passage. Model assumptions and possible violations are discussed. Releases of radio-tagged and passive integrated transponder (PIT) tagged steelhead smolts were also compared to assess the possible effects of tag type on migration behavior. Survival through the Rocky Reach project (P = 0.86) and Rock Island project (P = 0.41) and bypass diversion probabilities at Rocky Reach Dam (P = 0.39) were found to be similar between tag types. Small but significant differences in arrival patterns (P = 0.02) and travel times (P = 0.01) were observed between radio-tagged and PIT-tagged smolts.

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)0.000
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 score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.025
GPT teacher head0.236
Teacher spread0.211 · 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

Citations58
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→