MétaCan
Menu
Back to cohort

Exhaust Control, Industrial

2000· other· en· W1914522870 on OpenAlex
Ronald L. Berglund

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

VenueKirk-Othmer Encyclopedia of Chemical Technology · 2000
Typeother
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsIncinerationWaste managementCatalysisCombustionExhaust gasCatalytic combustionNitrogen oxidesChemical industryProcess engineeringPollutantEnvironmental scienceEngineeringChemistryEnvironmental engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Exhaust emissions are increasingly legislated. Much of the research and development in the chemical process, petroleum, power generation, and manufacturing industries is driven by the need to control exhausts utilizing post‐process emissions treatment. Oxidative combustion technology is commonly employed for elimination of volatile organic components. This technology may be strictly thermal (incineration) or employ oxidation catalysis. The catalysts, mechanistic models, and design, operation, and selection of industrial catalytic exhaust control systems are discussed, as is catalytic inhibition. Exhaust control technology for criteria air pollutants, such as the nitrogen oxides, is presented. The use of catalytic oxidation techniques for control of specific emissions within particular industries is also discussed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient 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: Other · Consensus signal: none
Teacher disagreement score0.522
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.008
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