MétaCan
Menu
Back to cohort
Record W2035392766 · doi:10.1577/m03-196.1

Evaluating the Effectiveness of Instream Habitat Structures for Overwintering Stream Salmonids: A Test of Underwater Video

2005· article· en· W2035392766 on OpenAlexafffundabout
Leah D. Carlson, Michael S. Quinn

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsOverwinteringHabitatSTREAMSEnvironmental scienceFisheryUnderwaterSampling (signal processing)Hydrology (agriculture)EcologyOceanographyComputer scienceGeologyBiology

Abstract

fetched live from OpenAlex

Abstract Instream habitat structures are often employed by fisheries managers to enhance habitat quality. The effectiveness of instream habitat structures, however, is hindered by a lack of critical and systematic assessment of their success, especially in winter conditions. This study tested the use of underwater video as a method to evaluate the use of instream habitat structures (V-weirs) by overwintering salmonids in the Crowsnest River of southwestern Alberta, Canada. The use of readily available and relatively inexpensive video equipment was shown to be effective in documenting salmonid use of winter habitat both under the ice and in open water. This technique may be particularly appropriate in areas where sampling mortality is a concern and where other methods are impractical or dangerous (e.g., small, ice-covered streams or rivers).

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)0.002
metaresearch head score (Gemma)0.006
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.014
GPT teacher head0.262
Teacher spread0.249 · 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

Citations6
Published2005
Admission routes3
Has abstractyes

Explore more

Same venueNorth American Journal of Fisheries ManagementSame topicFish Ecology and Management StudiesFrench-language works237,207