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Record W1970001992 · doi:10.1063/1.4754439

Determination of salinity gradient power potential in Québec, Canada

2012· article· en· W1970001992 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Renewable and Sustainable Energy · 2012
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsSalinityPower (physics)Osmotic powerPotential gradientEnvironmental scienceEnergy balanceBalanced flowEnergy (signal processing)Power BalanceWork (physics)Hydrology (agriculture)MeteorologyChemistryThermodynamicsMembraneOceanographyMathematicsPhysicsEngineeringGeologyStatisticsGeotechnical engineering

Abstract

fetched live from OpenAlex

Electrical energy can be produced from the chemical potential difference of two liquids with dissimilar salinities. This source of energy is known as salinity gradient power. In this paper, the theory, the technologies used to exploit the power, the major challenges, and their development trends are first presented. Then a modeling of fluxes across semi permeable membranes is proposed and validated. Next, an energy balance study is done in order to estimate the power potential for a given salinity gradient system. By applying this study to several rivers in Quebec, the salinity power gradient potential is estimated to 45 TWh/yr based on the minimal flow rate of each river.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.764

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.199
Teacher spread0.195 · 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