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Record W1963686894 · doi:10.1021/ef8010355

Ash Research from Palm Coast, Florida to Banff, Canada: Entry of Biomass in Modern Power Boilers<sup>†</sup>

2009· article· en· W1963686894 on OpenAlexaboutno aff
Flemming Frandsen

Bibliographic record

VenueEnergy & Fuels · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringLibrary scienceArchaeologyEnvironmental scienceGeographyComputer science

Abstract

fetched live from OpenAlex

For more than 40 years, regular worldwide conferences on ash and corrosion research have been held, in the beginning, within the framework of the United Engineering Foundation (UEF). The first conference was held in Marchwood, just outside Southampton in the UK in 1963, the next is coming up in Banff, Canada, in Autumn 2008. At the UEF ash conference in Palm Coast, FL, 1991, the late Dr. Richard Bryers provided an excellent outline of trends in ash research presented at these conferences in the period 1963−1991. Since 1991, ash conferences have been held in Solihull, UK, 1993; Waterville Valley, NH, 1995; Kona, HA, 1997; Park City, UT, 2000; and Snowbird, UT, 2001 and again in 2006. At the 1995 Waterville conference, the first papers on biomass-related ash research were provided. Since then, several aspects of utilization of biomass in power boilers have been addressed. It started out with pioneering release studies of alkali metals from biomass and a significant number of characterization as well as modeling studies. Later, a number of advanced analytical techniques, as well as detailed studies of deposition in all scales from the laboratory to full-scale, has been presented. This paper provides an outline of the trends in the papers presented, since the review by Bryers in 1991, and provides ideas on the direction of the research within this forum in the years to come.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.227
Teacher spread0.206 · 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 teacher head, not a consensus.

Study designObservational
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

Citations34
Published2009
Admission routes1
Has abstractyes

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