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Record W2184209239

AXIALT A SUCCESS STORY IN HYDRAULIC TURBINES RESEARCH

2013· article· en· W2184209239 on OpenAlexaboutno aff
Gabriel Dan Ciocan, Claire Deschênes

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsnot available
Fundersnot available
KeywordsHydraulic turbinesTurbinePropellerMarine engineeringHydraulic machineryExperimental dataEngineeringComputer scienceMechanical engineeringSystems engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper presents an overview of the AxialT project initiated in 2007 by the Laval University Consortium on Hydraulic Machines. The aim of this project was to improve the knowledge of hydraulic phenomena in a propeller turbine. Experimental, numerical and theoretical approach was employed. Modern experimental techniques as 2D-LDV, 3D-PIV, unsteady pressure probe and unsteady embedded pressure measurements using a telemetric data transmission system were used to qualify the flow in an axial turbine model. Specific methods were developed for the analysis of the experimental data and numerical simulation results. A database, shared between Consortium partners is available for future analysis.

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)0.020
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.005
Scholarly communication0.0100.010
Open science0.0020.006
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0110.005

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 head0.030
GPT teacher head0.289
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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