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Record W2461724569 · doi:10.1515/jnet-2016-0017

Multistage Pressure-Retarded Osmosis

2016· article· en· W2461724569 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

VenueJournal of Non-Equilibrium Thermodynamics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPressure-retarded osmosisSalinityOsmotic powerOsmosisReverse osmosisForward osmosisSalt (chemistry)Process (computing)Pressure gradientEnvironmental scienceProcess engineeringComponent (thermodynamics)Osmotic pressureEnergy (signal processing)Salt waterPetroleum engineeringEnvironmental engineeringMembraneChemistryComputer scienceEngineeringThermodynamicsMechanicsMathematicsGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract One promising sustainable energy source is the chemical potential difference between salt and freshwater. The membrane process of pressure-retarded osmosis (PRO) has been the most widely investigated means to harvest salinity gradient energy. In this report, we analyse the thermodynamic efficiency of multistage PRO systems to optimize energy recovery from a salinity gradient. We establish a unified description of the efficiencies of the component pumps (

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.234
Teacher spread0.226 · 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