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Record W7056504595

Experimental Research On Iron Combustion At Eindhoven University of Technology

2023· article· en· W7056504595 on OpenAlexaff

Bibliographic record

VenueTU/e Research Portal · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsAvalon Rare Metals (Canada)
FundersChina Scholarship CouncilNederlandse Organisatie voor Wetenschappelijk OnderzoekEuropean Commission
KeywordsExperimental researchCombustionLaminar flowParticle (ecology)Experimental dataWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

The recent years, intensive experimental studies on iron combustion have been carried out by researchers of Power and Flow group of Eindhoven University of Technology. This work has been aimed on providing deep understanding of physical processes relevant to applications of iron powder as recyclable energy carrier for storing and transportation of “green energy”, namely, for energy generation by iron powder combustion within a so-called “dry” cycle. Research has been performed with different experimental setups designed and built to study iron flames of different levels of complexity, ranging from “fundamental” single particle and laminar aerosol flames to pilot designs of industrial burners. A brief review of these experimental studies and their results is provided in this paper.

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 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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
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
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1300.002

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 head0.076
GPT teacher head0.391
Teacher spread0.314 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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