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Record W2000482085 · doi:10.1002/rem.20174

Treatment of Sydney N.S. tar pond sludge in a pilot‐scale rotary kiln

2008· article· en· W2000482085 on OpenAlexaffabout
Lei Jia, Edward J. Anthony

Bibliographic record

VenueRemediation Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsQueen's University
Fundersnot available
Keywordstar (computing)KilnWaste managementRotary kilnEnvironmental scienceCombustionEnvironmental chemistryChemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Tar pond wastes from Sydney, Nova Scotia, containing 50 ppm or more of polychlorinated biphenyls (PCBs) were treated in a pilot‐scale rotary kiln. In order to use the existing feed system attached to the rotary kiln, the wastes were first oven‐dried. Stack gas sampling was conducted during the test, which included measurement of volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), semi‐volatile organic compounds (SVOCs), HCl, and metals. The purpose of this study was to determine emissions from treatment of the tar pond waste using rotary kiln technology. It was found that the dried sludge could sustain combustion in the kiln without any supporting fuel. The emissions of polychlorinated dibenzodioxins/furans (PCDD/Fs) were higher than the Canadian Council of Ministers of the Environment (CCME) air emissions guidelines, and the reasons for this are discussed. © 2008 Wiley Periodicals, Inc.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.015
GPT teacher head0.208
Teacher spread0.194 · 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 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
Published2008
Admission routes2
Has abstractyes

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