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A quantitative assessment of fish passage efficiency

2011· article· en· W2145380083 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFish and Fisheries · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsWeirFisheryFish <Actinopterygii>Upstream (networking)Environmental scienceHabitatFragmentation (computing)Range (aeronautics)Upstream and downstream (DNA)BiologyHydrology (agriculture)EcologyGeographyEngineeringCartography

Abstract

fetched live from OpenAlex

Abstract In an attempt to restore the connectivity of fragmented river habitats, a variety of passage facilities have been installed at river barriers. Despite the cost of building these structures, there has been no quantitative evaluation of their overall success at restoring fish passage. We reviewed articles from 1960 to 2011, extracted data from 65 papers on fish passage efficiency, size and species of fish, and fishway characteristics to determine the best predictors of fishway efficiency. Because data were scarce for fishes other than salmonids (order Salmoniformes), we combined data for all non‐salmonids for our analysis. On average, downstream passage efficiency was 68.5%, slightly higher than upstream passage efficiency of 41.7%, and neither differed across the geographical regions of study. Salmonids were more successful than non‐salmonids in passing upstream (61.7 vs. 21.1%) and downstream (74.6 vs. 39.6%) through fish passage facilities. Passage efficiency differed significantly between types of fishways; pool and weir, pool and slot and natural fishways had the highest efficiencies, whereas Denil and fish locks/elevators had the lowest. Upstream passage efficiency decreased significantly with fishway slope, but increased with fishway length, and water velocity. An information‐theoretic analysis indicated that the best predictors of fish passage efficiency were order of fish (i.e. salmonids &gt; non‐salmonids), type of fishway and length of fishway. Overall, the low efficiency of passage facilities indicated that most need to be improved to sufficiently mitigate habitat fragmentation for the complete fish community across a range of environmental conditions.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.998

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)0.0030.000

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 head0.239
Teacher spread0.214 · 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