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River temperature dynamics downstream of a shallow reservoir: process-based modelling to evaluate thermal mitigation strategies

2020· article· en· W3084373761 on OpenAlexaff
Dan H. Moore, D.L. West

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHypolimnionSeicheEnvironmental scienceHydrology (agriculture)Water levelThermalHabitatOceanographyGeologyEcologyNutrientEutrophicationMeteorologyGeographyBiology

Abstract

fetched live from OpenAlex

This study focused on Alouette River, located in south coastal British Columbia. During summer, water is released from shallow reservoir at a near-constant rate from an outlet about 6-10 m below the water surface. Outlet temperatures in summer 2013 were initially cool hypolimnetic water, followed by alternating cool and warm water associated with an internal seiche, and finally dominated by warm epilimnetic water during the period of highest water temperature. An energy-balance model was used to evaluate potential strategies to ameliorate thermal habitat conditions for Pacific salmon downstream of the dam. Restoration of deforested banks that represented 4% of the reach length reduced daily maximum temperatures by only about 0.5 °C , while releasing more flow exacerbated temperatures during the warmest week of the year. The only effective strategy for thermal amelioration would be to release water from deeper in the reservoir.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.657

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.243
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations0
Published2020
Admission routes1
Has abstractyes

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