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Record W2086073390 · doi:10.1080/03632415.2011.616459

NSERC's HydroNet: A National Research Network to Promote Sustainable Hydropower and Healthy Aquatic Ecosystems

2011· article· en· W2086073390 on OpenAlex
Karen E. Smokorowski, Normand Bergeron, Daniel Boisclair, Keith D. Clarke, Steven J. Cooke, R. A. Cunjak, Jeff Dawson, Brett Eaton, Faye Hicks, Paul S. Higgins, Chris Katopodis, Michel Lapointe, Pierre Legendre, Michael Power, Robert G. Randall, Joseph B. Rasmussen, George A. Rose, Andre Saint‐Hilaire, Brent Sellars, Gary J. Swanson, Nicholas Winfield, Roger Wysocki, David Z. Zhu

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFisheries · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsManitoba HydroMcGill UniversityEnvironment and Climate Change CanadaFisheries and Oceans CanadaUniversity of British ColumbiaBC Hydro (Canada)Institut National de la Recherche ScientifiqueUniversity of LethbridgeUniversité de MontréalUniversity of New BrunswickNalcor Energy (Canada)University of AlbertaMemorial University of NewfoundlandUniversity of WaterlooGovernment of CanadaCarleton University
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsHydropowerAquatic ecosystemEnvironmental resource managementGovernment (linguistics)BusinessEcosystemSustainabilityProcess (computing)Environmental scienceEnvironmental planningEngineeringEcologyComputer scienceBiology

Abstract

fetched live from OpenAlex

Abstract NSERC's HydroNet is a collaborative national five-year research program initiated in 2010 involving academic, government, and industry partners. The overarching goal of HydroNet is to improve the understanding of the effects of hydropower operations on aquatic ecosystems, and to provide scientifically defensible and transparent tools to improve the decision-making process associated with hydropower operations. Multiple projects are imbedded under three themes: 1) Ecosystemic analysis of productive capacity offish habitats (PCFH) in rivers, 2) Mesoscale modelling of the productive capacity offish habitats in lakes and reservoirs, and 3) Predicting the entrainment risk of fish in hydropower reservoirs relative to power generation operations by combining behavioral ecology and hydraulic engineering. The knowledge generated by HydroNet is essential to balance the competing demands for limited water resources and to ensure that hydropower is sustainable, maintains healthy aquatic ecosystems and a vibrant Canadian economy. Resumen NSERC's HydroNet es un programa nacional colaborativo de investigación a cinco años que inició en el año 2010 e involucra a los sectores académico, gubernamental e industrial. El objetivo general de HydroNet es comprender los efectos que tienen las operaciones hidroeléctricas en los ecosistemas acuáticos y ofrecer herramientas científicas defendibles y transparentes tendientes a mejorar los procesos en la toma de decisiones que están asociados al uso de la energía hidroeléctrica. Diversos proyectos se encuentran insertos en tres grandes tópicos: 1) análisis ecosistémico de la capacidad productiva de los habitats para peces (CPHP) en ambientes fluviales, 2) Modelación de meso-escala de la capacidad productiva de los habitats para peces en lagos y embalses, y 3) predicción del riesgo de arrastre de peces hacia los embalses hidroeléctricos, en función del poder generador de las operaciones, combinando la ecología conductual y la ingeniería hidráulica. El conocimiento generado por HydroNet es fundamental para evaluar el balance entre la demanda por recursos hídricos limitados, para asegurar que la energía hidroeléctrica sea sustentable, que promueva la salud de los ecosistemas acuáticos así como también a la pujante economía canadiense.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.276
Teacher spread0.234 · 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